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. 2023 Mar 6;12:e85494. doi: 10.7554/eLife.85494

Transferred mitochondria accumulate reactive oxygen species, promoting proliferation

Chelsea U Kidwell 1,, Joseph R Casalini 1,, Soorya Pradeep 2, Sandra D Scherer 3, Daniel Greiner 1, Defne Bayik 4, Dionysios C Watson 4,5,6, Gregory S Olson 7, Justin D Lathia 4, Jarrod S Johnson 8, Jared Rutter 1,9,10, Alana L Welm 3, Thomas A Zangle 2,10, Minna Roh-Johnson 1,10,
Editors: Lydia WS Finley11, Benoît Kornmann12
PMCID: PMC10042539  PMID: 36876914

Abstract

Recent studies reveal that lateral mitochondrial transfer, the movement of mitochondria from one cell to another, can affect cellular and tissue homeostasis. Most of what we know about mitochondrial transfer stems from bulk cell studies and have led to the paradigm that functional transferred mitochondria restore bioenergetics and revitalize cellular functions to recipient cells with damaged or non-functional mitochondrial networks. However, we show that mitochondrial transfer also occurs between cells with functioning endogenous mitochondrial networks, but the mechanisms underlying how transferred mitochondria can promote such sustained behavioral reprogramming remain unclear. We report that unexpectedly, transferred macrophage mitochondria are dysfunctional and accumulate reactive oxygen species in recipient cancer cells. We further discovered that reactive oxygen species accumulation activates ERK signaling, promoting cancer cell proliferation. Pro-tumorigenic macrophages exhibit fragmented mitochondrial networks, leading to higher rates of mitochondrial transfer to cancer cells. Finally, we observe that macrophage mitochondrial transfer promotes tumor cell proliferation in vivo. Collectively these results indicate that transferred macrophage mitochondria activate downstream signaling pathways in a ROS-dependent manner in cancer cells, and provide a model of how sustained behavioral reprogramming can be mediated by a relatively small amount of transferred mitochondria in vitro and in vivo.

Research organism: Human, Mouse

Introduction

It has been previously described that mitochondria can undergo lateral transfer between cells (Torralba et al., 2016; Antanavičiūtė et al., 2014; Lou et al., 2012; Rebbeck et al., 2011; Tan et al., 2015; Wang and Gerdes, 2012; Wang and Gerdes, 2015; Lampinen et al., 2022). Mitochondria are dynamic organelles, known to provide energy for the cell, but more recently shown to have a variety of additional essential cellular functions (Zong et al., 2016). In animal models, a series of seminal studies revealed that cancer cells void of mitochondrial DNA still form tumors by obtaining mitochondria from stromal cells, thereby restoring cancer cell mitochondrial function, cellular respiration, and tumor formation (Tan et al., 2015; Dong et al., 2017). Other experiments suggest that mitochondrial transfer not only restores bioenergetics, but can alter the metabolic state of recipient cells (Brestoff et al., 2021; Nicolás-Ávila et al., 2020; Phinney et al., 2015; Saha et al., 2022; Crewe et al., 2021; Korpershoek et al., 2022; Liu et al., 2022; van der Vlist et al., 2022; Yang et al., 2022; Liu et al., 2021), allowing recipient cells to adapt to stressors or changes in the environment, prompting the development of methods targeting mitochondrial dysfunction in disease (Patel et al., 2023; Caicedo et al., 2015). Although these studies elegantly demonstrate that mitochondrial transfer alters recipient cellular behavior, many aspects of this process remain unclear. For instance, the rescue of cellular function is commonly attributed to enhanced mitochondrial energetic or metabolic profiles; however, the fate and function of transferred mitochondria in recipient cells are under-explored. Furthermore, it is unclear how cells respond to laterally transferred mitochondria if the recipient cells already have a fully functioning mitochondrial network, and in particular, if the transferred mitochondria only comprise a small subset of the overall mitochondrial network in the recipient cell.

Given that metastasis is a low-frequency event and is the consequence of changes in cellular behavior on the single-cell level, we aimed to examine the function and behavior of transferred mitochondria within individual recipient cells that have functioning endogenous mitochondrial networks. Using a combination of in vitro high-resolution microscopy, optogenetics, imaging flow cytometry, and in vivo tumor models, we demonstrate a previously undescribed mechanism of mitochondrial transfer-associated cellular reprogramming. Collectively, our data explain how a relatively small amount of transferred mitochondria can impact cellular behavior in the recipient cell with fully functioning endogenous mitochondria – Transferred macrophage mitochondria in cancer cells are dysfunctional, ROS accumulates at the site of transferred mitochondria, promoting ERK-mediated cancer cell proliferation.

Results

Cancer cells with macrophage mitochondria exhibit increased proliferation

We previously reported that macrophages transfer cytoplasmic contents to cancer cells in vitro and in vivo (Roh-Johnson et al., 2017), and hypothesized that a macrophage/cancer cell system would be ideal for probing mitochondrial transfer in cells with functioning mitochondrial networks. Our studies employed blood-derived human macrophages and a human breast cancer cell line, MDA-MB-231 (231 cells), stably expressing a mitochondrially localized mEmerald or red fluorescent protein (mito-mEm or mito-RFP, respectively; Figure 1a). We observed mitochondrial transfer from macrophages to 231 cells using live cell confocal microscopy (Figure 1b, arrowheads) and flow cytometry (Figure 1c–d; flow cytometry scheme in Figure 1—figure supplement 1a). Control gates were set to 0.2%, based on confirmation of mitochondrial transfer by FACS-isolation of distinct mEmerald+ populations (see methods for more information). With these methods, a range of transfer efficiencies were observed, which we attribute to donor-to-donor variability (Figure 1d), yet mitochondrial transfer was consistently observed in 231 cells, as well as to another breast cancer line, MDA-MB-468, and a melanoma cell line, A375 (Figure 1—figure supplement 1b). To determine whether macrophage mitochondrial transfer was unique to cancer cells, we tested a non-malignant breast epithelial cell line, MCF10A. We observed reduced mitochondrial transfer efficiencies to MCF10A cells, with no significant differences compared to control (Figure 1—figure supplement 1c), suggesting that macrophages exhibit higher mitochondrial transfer efficiencies to malignant cells. Transferred mitochondria contain a key outer mitochondrial membrane protein, TOMM20 (Figure 1—figure supplement 1d, arrowhead) and mitochondrial DNA (Figure 1—figure supplement 1e, arrowhead), suggesting that intact organelles are transferred to 231 cells. To better define the requirements for transfer, we performed trans-well experiments in which we cultured 231 cells either physically separated from macrophages by a 0.4 μm trans-well insert or in contact with macrophages (scheme in Figure 1—figure supplement 1f), or with conditioned media (Figure 1—figure supplement 1g, h). These data showed that mitochondrial transfer increased dramatically under conditions where 231 cells could contact macrophages directly (Figure 1—figure supplement 1g and h). Taken together, these results suggest that macrophage mitochondrial transfer to cancer cells likely requires cell-to-cell contact. Furthermore, while mitochondrial transfer may not be unique to cancer cells, macrophages transfer mitochondria to cancer cells at higher frequencies. Thus, due to the low rates of mitochondrial transfer across macrophage donors (0.84%, Figure 1d), we subsequently took advantage of single-cell, high-resolution approaches – rather than bulk approaches – to follow the fate and functional status of transferred mitochondria.

Figure 1. Cell-contact-mediated transfer of macrophage mitochondria leads to increased cancer cell proliferation.

(a) CD14+ monocytes harvested from human blood are transduced and differentiated for 6 days. Mito-mEm +macrophages (green) are co-cultured with MDA-MB-231 cells (231 cells) expressing mito-RFP (magenta; right image). (b) Confocal image showing transferred mitochondria (green, arrowhead) in a 231 cell (magenta, cell outline in white). (c) Representative flow cytometry plots depicting mitochondrial transfer (black box) within a population of co-cultured mito-RFP+ 231 cells (right) compared to monoculture control (left) with background level of mEmerald (mEm) fluorescence set at 0.2%. (d) Aggregate data of mitochondrial transfer rates across macrophage donors. Each data point represents one replicate (N=14 donors). (e) Analysis of proliferative capacity by quantifying Ki-67 levels and DNA content in co-cultured 231 cells after 24 hr. Percentage of cancer cells within a specific cell cycle phase with or without transfer is shown. A significantly different percent of recipient cells occupies G2/M (black) phases of the cell cycle compared to non-recipient cells (N=4 donors; statistics for G2/M only). (f) Co-cultured recipient 231 cells have a significantly higher specific growth rate compared to non-recipients (N=60 cells (control), 115 (recipient) over 4 donors indicated as shades of gray). (g) Schematic of mitochondrial isolation and bath application on MDA-MB-231 cells. Mitochondria are isolated from mito-mEmerald expressing THP-1 monocytes and bath applied at 20–30 µg/mL for 24 hr. Cancer cells which had taken up mEm+ mitochondria are then FACS-isolated and plated for 48 hr for further analyses. (h) Representative confocal image showing mito-RFP-expressing 231 cell (magenta) that had taken up macrophage mitochondria (green, grey arrow). (i) 48 hr after FACS-isolating 231 cells with macrophage mitochondria, flow cytometry was used to determine percent of daughter cells which still contain mEm+ mitochondria. N=3 biological replicates. (j), Cell cycle analysis of daughter cells 48 hr after FACS-isolation of 231 cells that had taken up macrophage mitochondria. N=3 biological replicates. For all panels, standard error of the mean (SEM) is displayed and scale bars are 10 µm. Mann-Whitney (d), two-way ANOVA (e, j), Welch’s t-test (f, i), *p<0.05; **p<0.01; ****p<0.0001.

Figure 1.

Figure 1—figure supplement 1. Macrophages transfer mitochondria to cancer cells.

Figure 1—figure supplement 1.

(a) Representative flow cytometry plots of mito-RFP MDA-MB-231 monocultured cells used as a control (top) and mito-RFP 231/mito-mEm macrophage co-cultures after 24 hr (bottom). (b) Panel of cancer cell lines – MDA-MB-231 (‘231’), MDA-MB-468 (‘468’) and A375 – co-cultured with mEm-positive (transduced, ‘+’) or mEm-negative (untransduced, ‘-’) macrophages. Mitochondrial transfer rates determined by flow cytometry, as described in (a). Different donors (N=3) indicated as shades of gray. (c) Left: Bar graph quantifying mitochondrial transfer to MCF10A cells after 24 hr. (N=3 donors indicated by shades of gray). Right: Confocal image showing macrophage mitochondria (green, arrowhead) in a MCF10A cell (magenta). (d) Stills from a time-lapse showing a 231 cell (mCherry-TOMM20, magenta) containing transferred macrophage mitochondria (mEmerald-TOMM20, green, arrowhead). Timepoints indicated in upper left. (e) Single Z-plane of a 231 cell labeled with mitochondrial dye TMRM (magenta) with macrophage mitochondria (green, arrowhead) containing DNA (gray). 83% of transferred mitochondria contain DNA (N=16 cells). (f) Schematic depicting trans-well experiments. 231 cells (magenta) were plated alone (left), separated from macrophages (green; middle), or plated together (right). (g) Percent of cancer cells with transfer in conditions depicted in f, (N=3 donors). (h), Conditioned media (CM) experiments showing percent of cancer cells with transfer when co-cultured in media type listed on the x-axis (N=2 experiments). Each dot represents one replicate for all panels. Error bars represent standard error of the mean (SEM) and scale bars are 10 µm. Two-way ANOVA (b, g), Mann-Whitney test (c), ****p<0.0001.
Figure 1—figure supplement 2. Cancer cells will macrophage mitochondria exhibit increased proliferation.

Figure 1—figure supplement 2.

(a) Cancer cells and macrophages were cocultured for 24 hours and scRNA-seq was performed. Ingenuity Pathway Analysis of scRNA-seq data reveals significant changes in canonical cell proliferation pathways in co-cultured cancer cells that received macrophage mitochondria compared to co-cultured cancer cells that did not. (b) Representative flow cytometry plots of mito-RFP 231/mito-mEm macrophage co-cultures stained for Ki67 and DNA content. (c) 24 hr data from Figure 1e but separated as percent of cancer cells in each phase of the cell cycle with (triangle) or without transfer (circle). (d) 48 hr of co-culture as described in (c) with aggregate data in stacked bar graphs to the right (stats displayed for G2/M only). Each pair in (c) and (d) represents cells within one technical replicate and each donor is represented by color (N = 4 donors for both data sets). (e) Time-lapse imaging was used to quantify the amount of co-cultured 231 cells that did (black) or did not complete (gray) cytokinesis over a 48-hr period (N = 416 cells, 4 donors). Error bars represent SEM. Two-way ANOVA (c–e), ***p<0.001; ****p<0.0001.
Figure 1—figure supplement 3. Mitochondrial transfer leads to sustained increased growth rate in daughter cancer cells.

Figure 1—figure supplement 3.

(a) QPI data of mass over time measurements for a single triad consisting of one parent cell (black) and two daughters that inherited (gray) or did not inherit (light gray) the parent’s macrophage mitochondria. Specific growth rate (slope of best fit line normalized by average mass) is listed next to line trace of corresponding cell. (b) QPI data of specific growth rate of 5 individual triads (indicated by color). Parent and daughter cells are indicated with shape (legend on graph). (c) QPI data of normalized mass in picograms (pg) over time in hours (hrs) for daughter cells that did (black) or did not (gray) inherit the parent’s macrophage mitochondria normalized to daughter cell initial mass. Error bars represent SEM. (d) Cell cycle analyses MDA-MB-231/macrophage co-cultures after 24 hr 1 µM Palbociclib treatment. Two-way ANOVA comparing G1/G0 fractions in each condition, ****p<0.0001. When comparing G2/M fractions across conditions **p=0.0017. n=1 in technical triplicate. (e) MDA-MB-231/macrophage cocultures were treated with 10 µM Palbociclib for 24 hr. Mitochondrial transfer rates were determined via flow cytometry as previously described. Unpaired t-test p=0.4675, n=1 in technical triplicate.

To determine the effects of macrophage mitochondrial transfer on cancer cells, we performed single cell RNA-sequencing on cancer cells that received macrophage mitochondria. These data revealed that mitochondrial transfer induced significant changes in canonical cell proliferation-related pathways (Figure 1—figure supplement 2a). To follow up on the RNA-sequencing results, we used flow cytometry to evaluate proliferation changes, and found significant increases in the percent of cells within the G2 and Mitotic (M) phases of the cell cycle in recipient cells, as compared to their co-cultured counterparts that did not receive mitochondria (Figure 1e; Figure 1—figure supplement 2b-d). These cells were not undergoing cell cycle arrest, as we found that recipient cells completed cytokinesis at rates equivalent to their co-cultured non-recipient counterparts (Figure 1—figure supplement 2e). For further confirmation of this proliferative phenotype, we used quantitative phase imaging (QPI) to detect changes in dry mass of co-cultured 231 cells over time (Zangle and Teitell, 2014). With this approach, we could obtain growth rate information of a large number of cancer cells over time (n=60 control cells; n=115 recipient cancer cells). Consistent with the flow cytometry-based cell cycle analysis, the specific growth rates increased significantly in 231 cells with macrophage mitochondria compared to 231 cells that did not receive mitochondria (Figure 1f). To examine whether the effects of mitochondrial transfer was sustained in recipient cells, we also measured the growth rates of daughter cells born from recipient 231 cells containing macrophage mitochondria (Zangle et al., 2014). We identified five ‘parent’ cancer cells with macrophage mitochondria, for which we were able to reliably follow both daughter cells upon division. Daughter cells that inherited the ‘parent’s’ macrophage mitochondria exhibited an increase in their rate of change of dry mass over time versus sister cells that did not inherit macrophage mitochondria (Figure 1—figure supplement 3a-c). These experiments indicate that the proliferation phenotype in recipient cancer cells is sustained.

Our results so far suggest that either macrophage mitochondrial transfer increases cancer cell proliferation, or that more proliferative cells are simply more capable of receiving macrophage mitochondria. Thus, to test between these hypotheses, we first blocked cells in the G1-phase of the cell cycle by treating co-cultures with a CDK4/6 inhibitor, Palbociclib (Figure 1—figure supplement 3d), and we observed no changes in mitochondrial transfer rates (Figure 1—figure supplement 3e). These data indicate that the enhanced proliferation observed in recipient cells is not due to proliferative cells more readily receiving transfer.

We then performed experiments to rigorously test whether transferred macrophage mitochondria causes cancer cell proliferation, rather than mitochondrial receipt and proliferation being correlative events in cancer cells. We also wanted to determine whether the observed proliferative phenotype is due to macrophage mitochondria, and not other molecules that are passed along with the macrophage mitochondria. Thus, we biochemically purified mitochondria from a macrophage cell line, THP-1, and directly applied these macrophage mitochondria to cancer cells for 24 hr (Figure 1g). We then FACS-isolated cancer cell populations that contained purified macrophage mitochondria, and allowed this population to undergo additional rounds of cell division, and then reanalyzed the proliferative capacity of cancer cells that had retained the macrophage mitochondria versus cancer cells that had lost the macrophage mitochondria over this time. We first confirmed that cancer cells retained the macrophage mitochondria by imaging (Figure 1h). We also found that cancer cells that had retained the macrophage mitochondria exhibited an increased percentage of cells in the G2/M phase of the cell cycle compared to cancer cells that had lost the macrophage mitochondria (Figure 1i-j). Together with the QPI results, these results support the model that macrophage mitochondrial transfer promotes a sustained pro-growth and proliferative effect in both recipient and subsequent daughter cells.

Transferred mitochondria are dysfunctional and accumulate ROS

We next sought to understand how donated mitochondria can stimulate a proliferative response in recipient cells. We performed time-lapse confocal microscopy on co-cultures and found that in cancer cells with macrophage mitochondria, macrophage-derived mito-mEm+ mitochondria remained distinct from the recipient host mitochondrial network. Cancer cells were cocultured with macrophages for 12 hr and subjected to an additional 15 hr of timelapse microscopy, and we observed no detectable loss of the fluorescent signal at transferred mitochondria throughout the course of imaging (Figure 2a, arrowhead; Video 1). Thus, transferred macrophage mitochondria did not appear to fuse with the existing endogenous mitochondrial network in recipient cells. To probe the functional state of the donated mitochondria, we performed live imaging with MitoTracker Deep Red (MTDR), a cell-permeable dye that is actively taken up by mitochondria with a membrane potential (Poot et al., 1996). To our surprise, all of the transferred mitochondria were MTDR-negative (Figure 2b, top left). This was also confirmed using a different mitochondrial membrane potential-sensitive dye, Tetramethylrhodamine Methyl Ester (TMRM; Figure 1—figure supplement 1e). These results suggested that the transferred mitochondria lacked membrane potential. To determine whether these membrane potential-deficient transferred mitochondria were subjected to lysosomal degradation, we labeled lysosomes and acidic vesicles with a dye, LysoTracker, and found that the majority of transferred mitochondria (57%) did not co-localize with the LysoTracker signal (Figure 2b, top right). The status of transferred mitochondria was unexpected because mitochondria typically maintain strong membrane potentials, and dysfunctional mitochondria that lack membrane potential are normally degraded or repaired by fusion with healthy mitochondrial networks (Phinney et al., 2015). Next, we utilized another dye which stains cellular membranes, MemBrite, and observed that 91% of transferred mitochondria were not encapsulated by a membranous structure, thus also excluding sequestration as a mechanism for explaining the lack of degradation or interaction with the endogenous mitochondrial network (Figure 2—figure supplement 1a). These data, taken together with the long-lived observation of the transferred mitochondria in Figure 2a, suggest that transferred macrophage mitochondria lack membrane potential, yet remain as a distinct population in recipient cancer cells, not fusing with the endogenous host mitochondrial network nor subjected to degradation.

Figure 2. Transferred macrophage mitochondria are long-lived, depolarized, and accumulate reactive oxygen species, promoting cancer cell proliferation.

(a) Stills from time-lapse imaging depicting the longevity of the transferred mitochondria (green, arrowhead) within a 231 cell (magenta, cell outline in white). Time elapsed listed in left corner. (b) Confocal image of a mito-RFP+ 231 cell (magenta) containing macrophage mitochondria (green, arrowhead) stained with MTDR (yellow) and LysoTracker (teal). MTDR does not accumulate in 100% of donated mitochondria (N=25 cells, 5 donors). Majority (57%) of donated mitochondria do not colocalize with LysoTracker signal (N=24 cells, 4 donors). (c) Ratiometric quantification of mito-Grx1-roGFP2 biosensor mapped onto the recipient 231 cell with fire LUT (top panel). Confocal image of mito-Grx1-roGFP2-expressing 231 cell (bottom right, green and yellow) containing a macrophage mitochondria (bottom left, red, arrowhead). (d) Ratiometric measurements of the mito-Grx1-roGFP2 sensor per 231 cell (paired dots) at a region of interest containing the host mitochondrial network (host) or a transferred mitochondria (transfer). Cells were co-cultured for 24 hr (N=27 cells, 3 donors indicated in shades of gray). (e) Exogenous purified macrophage mitochondria (green) is void of mitochondrial membrane potential (MitoTracker Deep Red-negative, yellow, arrowhead) in cancer cells. (f) Cell cycle analysis of cancer cells with exogenous purified macrophage mitochondria versus sister cells that did not take up exogenous purified mitochondria, either treated with vehicle or 100 μM mitoTEMPO (mitochondrially-targeted superoxide scavenger. N=3 donors; statistics for G2/M only). (g) Schematic of optogenetic experiments to generate data in (h). Cells expressing mito-KillerRed are photobleached in a specific ROI containing either cytoplasm only (left) or mito-KillerRed+ mitochondria (right). Following photobleaching, cells are imaged over time to quantify the amount of cell division. (h) Quantification of cell division after photobleaching. Each data point is the average within a field of view (N=13 experiments), with control (cyto) and experimental (mito) data shown as paired dots per experiment. Scale bars are 10 µm. Wilcoxon matched-pairs signed rank test (d, h), two-way ANOVA (f), *p<0.05; ****p<0.0001.

Figure 2.

Figure 2—figure supplement 1. Transferred mitochondria accumulate reactive oxygen species, and internalized exogenous mitochondria are not encapsulated in a membrane compartment.

Figure 2—figure supplement 1.

(a) Recipient 231 cells were stained with a dye, MemBrite, that marks both the plasma and vesicular membranes. 91% of transferred mitochondria (green, arrowheads) did not co-localize with MemBrite signal (magenta, left panel) whereas 9% did (right panel) (N=11 cells, 1 donor). (b) Ratiometric measurements of the mito-Grx1-roGFP2 sensor per 231 cell (paired dots) at a region of interest (ROI) containing the recipient host mitochondrial network (host) or a transferred mitochondria (transfer). Cells were co-cultured with macrophages for 48 hr (N=37 cells, 3 donors), individual donors are indicated as shades of gray. (c) Ratiometric quantification of mito-roGFP2-Orp1 biosensor mapped onto recipient 231 cell in the fire LUT (top). Bottom left panel shows macrophage mitochondria (bottom left, red, arrowhead) and bottom right shows mito-roGFP2-Orp1 (green and yellow). (d) Ratiometric measurements of the mito-roGFP2-Orp1 sensor per 231 cell (paired dots) at a ROI containing the host mitochondrial network (host) or a transferred mitochondria (transfer). Cells were co-cultured with macrophages for 24 hours (N=21 cells, 3 donors, left) or 48 hr (N=26 cells, 3 donors, right).( e), Mitochondria were isolated from mito-mEm expressing THP-1 cells. The purified mitochondrial preparations (green) were perfused onto MDA-MB-231 cells expressing mito-RFP (magenta). 24 hr after mitochondrial uptake, MDA-MB-231 cells were stained with MemBrite (cyan) to visualize membranes. Longer incubations with MemBrite stain allow for visualization of internal membrane structures (intracellular cyan-positive structures in the image), and internalized exogenous mitochondria did not colocalize with MemBrite staining (arrowheads). Individual donors are indicated as shades of gray. All scale bars are 10 μm. Wilcoxon matched-pairs signed rank test (b, d), **p<0.01; ***p<0.0001.
Figure 2—figure supplement 2. Inducing reactive oxygen species results in cancer cell proliferation.

Figure 2—figure supplement 2.

(a) Photobleaching a region of interest (ROI; blue) containing KillerRed + mitochondria (top panels) generate an increase in ROS levels (DCFDA, ROS indicator, bottom panels). Mean fluorescent intensity (MFI) of DCFDA list in the inset. (b) Schematic of optogenetic experiments to generate data in Figure 2g and h and Figure 3c and d. Cells expressing mito-KillerRed are photobleached in a specific ROI containing either cytoplasm only (left) or mito-KillerRed+ mitochondria (right). Following photobleaching, cells are imaged over time to quantify the amount of cell division (Figure 2g and h) or ERK activity (Figure 3c and d). (c) Data from Figure 2h plotted next to an additional control. Quantification of percent cells divided after no stimulation (left column), photobleaching an ROI containing cytoplasm (cyto, middle column), or an ROI containing mito-KillerRed+ mitochondria (mito, right column). Each data point is the average within a field of view per condition (N=13 experiments). Error bars represent SEM and scale bars are 10 μm. Wilcoxon matched-pairs signed rank test, *p<0.05.

Video 1. Macrophage mitochondria are long-lived and remain distinct in recipient cancer cells.

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Video depicting a recipient mito-RFP expressing 231 cell (magenta) that contains mito-mEm macrophage mitochondria (green in magenta cell, center of frame). 231 cells were co-cultured with macrophages for 7 hr prior to the start of imaging for a duration ~15 hr with a time interval of 5 min. Maximum intensity projections of images are displayed at 12 frames per second, timestamp in upper left corner in hours (h), and scale bar is 10 μm.

Given the surprising observation that transferred mitochondria lack membrane potential, we hypothesized that instead of providing a metabolic or energetic advantage, the donated mitochondria may act as a signal source to promote sustained changes in cancer cell behavior. This hypothesis could offer insight into how this rare event, in which a relatively small amount of mitochondria is transferred, could mediate sustained changes in the proliferative capacity of recipient cancer cells. One signaling molecule associated with mitochondria is reactive oxygen species (ROS), which occur normally as byproducts of mitochondrial respiration, and can be produced at high levels during organellar dysfunction (Schieber and Chandel, 2014). Using a genetically encoded biosensor, mito-Grx1-roGFP2, as a live readout of the mitochondrial glutathione redox state (Gutscher et al., 2008), we found that after 24 and 48 hr, significantly higher ratios of oxidized:reduced protein were associated with the transferred mitochondria versus the host network (Figure 2c–d; Figure 2—figure supplement 1b). These data indicate that transferred macrophage mitochondria in recipient cells are associated with higher levels of oxidized glutathione, suggesting that they are accumulating higher amounts of ROS. Consistent with these results, a second biosensor that is specific for the reactive oxygen species H2O2, mito-roGFP2-Orp1 (Gutscher et al., 2009), also reported more oxidation at the transferred mitochondria compared to the host network (Figure 2—figure supplement 1c–d) after 48 hr of co-culture. At 24 hr, we observed a similar trend, but no statistically significant difference (Figure 2—figure supplement 1d). These results indicate that ROS accumulate at the site of transferred mitochondria in recipient cancer cells. It is unclear whether the observed ROS accumulation is generated by the transferred mitochondria themselves, or generated elsewhere in the recipient cancer cell and accumulating locally at transferred mitochondria. Regardless of the source, we observed robust ROS accumulation specifically at the site of transferred mitochondria and with this unexpected finding, we next tested whether this ROS accumulation could serve as a molecular signal, regulating cell proliferation.

To rigorously test the model that transferred macrophage mitochondria accumulate ROS, promoting cancer cell proliferation, we turned toward purified macrophage mitochondria approaches as in Figure 1g and sought approaches to reduce ROS levels. First, to better model the macrophage mitochondrial transfer to cancer cells that occurs in coculture conditions, we determined conditions for cancer cells to internalize exogenous macrophage mitochondria at rates similar to in vitro mitochondrial transfer conditions at 24 hr – 0.68% ± 0.36% internalization rate, n=3 biological replicates (compare to Figure 1d). We next determined that purified mitochondria taken up by cancer cells remain distinct, are not encapsulated by membranes after 24 hr (Figure 2—figure supplement 1e), and do not exhibit membrane potential (Figure 2e). Similar to our previous proliferation results with purified macrophage mitochondrial uptake at longer time points (Figure 1j), we found that cancer cells with internalized purified macrophage mitochondria (which, under these conditions, comprise ~1% of the total population) exhibited a significant increase in proliferative cells in the G2/M phase of the cell cycle, compared to sister cells that did not internalize mitochondria (Figure 2f, comparing black bars in lanes 1&2), and that this increase was ameliorated when ROS is quenched with a mitochondrially localized superoxide scavenger, mitoTEMPO (Figure 2f; comparing black bars in lanes 2&4). Importantly, cancer cells that did not internalize mitochondria were not affected by ROS quenching (Figure 2f; comparing black bars in lanes 1&3). These results indicate that transferred mitochondria promote proliferation in a ROS-dependent manner.

To test whether ROS accumulation can induce cancer cell proliferation directly, we stably expressed a mitochondrially localized photosensitizer, mito-KillerRed, which generates ROS when photobleached with 547 nm light (Bulina et al., 2006). As expected, photobleaching mito-KillerRed+ regions of interest induced ROS (Bass et al., 1983; Figure 2—figure supplement 2a). We then drew mito-KillerRed+ regions of interest that mimicked the size of macrophage mitochondrial transfer to induce local ROS in cancer cells, and analyzed the rate of cell division by imaging these cells over 18 hr (Figure 2g). We found that cells with induced ROS (by photobleaching mito-KillerRed+ regions) exhibited an increased percentage of dividing cells compared to negative control photobleached cells (mito vs. cyto bleach; Figure 2h; Figure 2—figure supplement 2b–c). These results indicate that induction of mitochondrially localized ROS can directly promote cancer cell proliferation.

ROS accumulation leads to ERK-dependent proliferation

We next aimed to determine how ROS induction may regulate cell proliferation. ROS is known to induce several downstream signaling pathways (Schieber and Chandel, 2014; Brillo et al., 2021), including ERK/MAPK signaling, a pathway known to regulate proliferation and tumorigenesis (Dhillon et al., 2007). Thus, we sought to determine if cancer cells that had received macrophage mitochondria exhibited increased ERK signaling. We stably expressed the ERK-Kinase Translocation Reporter (ERK-KTR) (Regot et al., 2014), which translocates from the nucleus to the cytoplasm when ERK is activated, in 231 cells (231-ERK-KTR). After co-culturing 231-ERK-KTR cells with macrophages, we used the imaging flow cytometer, Amnis ImageStream, to compare relative ERK-KTR translocation values in hundreds of cells that had or had not received macrophage mitochondria (ERK-KTR quantification and ERK signaling validation described in Figure 3—figure supplements 12). These data show that cancer cells with macrophage mitochondria have significantly higher cytoplasmic to nuclear (C/N) ERK-KTR ratios compared to cells that did not receive mitochondrial transfer, indicating increased ERK activity (Figure 3a–b; Figure 3—figure supplement 2a–b).

Figure 3. Recipient cancer cells exhibit ERK-dependent proliferation.

(a) ImageStream was used to measure the MFI of an ERK-Kinase Translocation Reporter (ERK-KTR, orange) in the nucleus (DAPI, blue) or cytoplasm of co-cultured 231 cells that did (right) or did not (left) receive mitochondria (green, arrowhead). Below: representative line scans (white dotted lines) of ERK-KTR (orange) and DAPI (blue). (b) Average ERK activity from data displayed in (d) (cytoplasm/nucleus (C/N) mean fluorescence intensity (MFI); N=3 donors indicated as shades of gray). (c) Confocal images of 231 cells expressing ERK-KTR (green) and Mito-KillerRed (magenta) with Hoechst 33342 (blue), after control cytoplasmic bleach (cyto, left) or mito-KillerRed+ bleach (mito, right). Below: representative line scans (white dotted lines) of ERK-KTR (green) and Hoechst (blue). (d) Quantification of ERK-KTR translocation 40 min post-bleach (cyto vs. mito), normalized to time 0. Each dot represents a measurement from a single cell. (e) Analysis of proliferative capacity by quantifying Ki-67 and DNA levels of co-cultured 231 cells treated with vehicle or ERK inhibitor (ERKi) with or without transfer or (f), mitochondrial internalization after mitochondrial bath application (N=3 donors; statistics for G2/M only). Error bars represent SEM and scale bars are 10 µm., Welch’s t-test (b), Mann-Whitney (d), two-way ANOVA (e–f), *p<0.05; **p<0.01; ****p<0.0001.

Figure 3.

Figure 3—figure supplement 1. Amnis ImageStream pipeline for ERK-KTR quantification.

Figure 3—figure supplement 1.

(a) Schematic of ERK-Kinase Translocation Reporter (KTR). When ERK activity is low, the fluorescent protein of the KTR resides primarily in the nucleus (left, dark gray). When ERK activity is high, the fluorescent protein translocates to the cytoplasm (right). (b) Workflow of Amnis ImageStream analyses. Mito-mEm macrophages and ERK-KTR-mRuby 231 cells were co-cultured for 24 hr and then analyzed on the ImageStream. Single cells in focus are selected and populations of interest can be isolated for further analyses. Representative images of recipient cells within our ‘transfer’ gate are displayed in all channels acquired (bottom right images). All populations of interest are then put though two independent readouts of KTR translocation: the pre-built IDEAS Similarity Wizard and/or the custom-built cytoplasmic:nuclear (cyto:nuc) mRuby mean fluorescent intensity masking algorithm. Scale bar is 10µm.
Figure 3—figure supplement 2. ERK-KTR analysis and validation using the Amnis ImageStream pipeline.

Figure 3—figure supplement 2.

(a) Representative ImageStream images using the mRuby mean fluorescence intensity (MFI) masking algorithm to quantify the amount of cytoplasmic cyto (cyto, C) and nuclear (nuc, N) ERK-KTR-mRuby. Representative images of translocated (left) and non-translocated (right) ERK-KTR images are displayed with the ratiometric cyto/nuc values listed below the corresponding images. (b) Representative ImageStream images using the IDEAS Similarity Wizard to quantify how similar ERK-KTR fluorescent signal is to the nuclear signal (DAPI). Representative images are displayed showing examples of translocated (left) and non-translocated (right) images with the ratiometric values listed below the corresponding images. (c) Quantification of ERK-KTR translocation in 231 monocultures using ImageStream after treatment with 1 μM of an ERK inhibitor (ERKi), SCH772984, or an ERK stimulator, Phorbol 12-myristate 12-acetate (PMA). Cyto/Nuc MFI of ERK-KTR (left) and similarity scores (right) for the same data set are displayed (N=1 donor). Scale bars are 10µm. One-way ANOVA, **p<0.01; ****p<0.0001.
Figure 3—figure supplement 3. Quantification of ERK activity in recipient 231 cells or upon ROS induction.

Figure 3—figure supplement 3.

(a) Cytoplasmic/Nuclear mean fluorescence intensity (C/N MFI) ratios of the ERK-KTR in co-cultured 231 cells are displayed for three different macrophage donors (N=3 experiments). Each data set shows an increase in C/N MFI ratios in recipient cells (left column on each plot) indicating higher ERK activity compared to their non-recipient co-cultured counterparts. (b) The same three experimental samples from the analyses in (a) were analyzed using the IDEAS Similarity Wizard. This analysis indicates cells that receive transfer (right column on each plot) have a lower similarity score, indicating higher ERK activity compared to cells that did not receive transfer (N=3 experiments). (c) Quantification over time of ERK-KTR translocation after mito bleach (black circles) compared to control cyto bleach (gray squares). Welch’s t-test (a–b), Two-way ANOVA at time point 40 min (c), ****p<0.0001.
Figure 3—figure supplement 4. ERK inhibition reduces proliferation in cancer cells with macrophage mitochondria.

Figure 3—figure supplement 4.

(a) Co-cultured 231 cells treated with 1 μM ERKi or vehicle at time of plating were analyzed for ERK-KTR translocation. Data are displayed from 3 different macrophage donors (N=3 experiments). Treatment with ERKi significantly reduced the amount of ERK activity in cells that did or did not receive transfer. (b) Average ERK activity from all experiments shown in (a) is displayed (N=3 donors). (c) Co-cultured macrophages and 231 cells were treated with 1 μM ERKi or vehicle at time of plating. Flow cytometry was used to determine how treatment influenced the cell cycle. Plots compare 231 cells that did (right) and did not (left) receive macrophage mitochondria in each stage of the cell cycle treated with vehicle (triangles) or ERKi (circles) (N=3 donors in technical triplicate). (d) Co-cultured 231 cells were treated with ERKi or vehicle at time of plating and the rate of mitochondrial transfer was determined with flow cytometry (N=3 donors in technical triplicate). For all panels, individual donors are indicated as shades of gray and error bars represent SEM. One-way ANOVA (a), two-way ANOVA (b–d), *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001.

Due to our observations that cells that receive macrophage mitochondria exhibit increased ERK activation and that local ROS induction is sufficient to induce cell proliferation, we then asked whether cancer cell mitochondrial ROS would directly enhance ERK activation. By expressing both mito-KillerRed and ERK-KTR in 231 cells, we induced ROS by photobleaching mito-KillerRed+ regions and found that ROS induction increased ERK-KTR translocation, indicating that ROS induction is sufficient to increase ERK activity in cancer cells (Figure 3c–d; Figure 3—figure supplement 2c). We next tested whether ERK signaling is required for the mitochondrial transfer-induced cancer cell proliferation. We first determined an effective concentration of SCH772984, an ERK inhibitor (ERKi), that still inhibits ERK activity, but does not dramatically affect 231 proliferation, as we sought to determine whether inhibiting ERK affects mitochondrial transfer-induced proliferation, not proliferation more generally. We first confirmed that treatment with this effective concentration of ERKi led to decreased ERK activity, as determined by the ERK-KTR translocation reporter (Figure 3—figure supplement 4a–b). We then found that treatment with ERKi significantly decreased proliferation of recipient 231 cells when compared to vehicle control-treated recipient cells (Figure 3e; Figure 3—figure supplement 4c). We further noted that the decrease in proliferation with this concentration of ERK inhibitor was observed only in cancer cells that received macrophage mitochondria, and not in cancer cells that did not receive macrophage mitochondria (bars 2&4 in Figure 3e, compared to bars 1&3), suggesting that the ERK-dependent cell proliferation specifically occurs in cancer cells that received mitochondrial transfer. As a control, we also confirmed that ERKi treatment did not alter mitochondrial transfer efficiencies, showing that ERK signaling does not influence mitochondrial transfer (Figure 3—figure supplement 4d). Finally, similarly to Figure 2f, we bath applied purified macrophage mitochondria to cancer cells in the presence of vehicle or ERKi and compared the proliferative capacity of cells that had internalized macrophage mitochondria versus cells that did not (Figure 3f). We found that, as before, uptake of purified macrophage mitochondria increased the percentage of cancer cells in the G2/M phase of the cell cycles (Figure 3f, bars 1&2), but that this process is ameliorated by the inhibition of ERK signaling (Figure 3f, bars 2&4). We also found that ERK inhibition did not affect the cell cycle state of cancer cells that had not taken up purified macrophage mitochondria (Figure 3f, bars 1&3). Thus, these results indicate that mitochondrial transfer promotes cancer cells proliferation through a ROS/ERK-dependent mechanism.

M2-like macrophages exhibits enhanced mitochondrial transfer rates

In many solid tumors, it has long been appreciated that macrophage density is associated with disease progression and poor patient prognosis (Pollard, 2004). Macrophages are highly plastic, altering their phenotypes, expression profiles and function, depending on environmental stimuli and conditional requirements (Pan et al., 2020). Accordingly, macrophages exist in a spectrum of activation states but are canonically simplified by the two ends of spectrum: pro-inflammatory and anti-tumorigenic M1-like macrophages; or anti-inflammatory and pro-tumorigenic M2-like macrophages (Huang et al., 2018). Since the ways in which M2-like macrophages promote tumor progression continue to be elucidated and given that there remains a dearth of understanding of how donor cell biology affects mitochondrial transfer, we aimed to determine how macrophage activation status affects intracellular mitochondrial dynamics and transfer efficiencies to cancer cells.

Activated macrophages were co-cultured with 231 cells, and we first quantified mitochondrial networks using Mitochondrial Network Analyses (MiNA) (Valente et al., 2017). We found that M2-like macrophages contain significantly more fragmented mitochondria when compared to M1-like or M0 (non-activated) macrophages (Figure 4a–b; Figure 4—figure supplement 1a–d). We then co-cultured 231 cells with either M0, M1-like, or M2-like macrophages and using flow cytometry, we found that mitochondrial transfer efficiencies were significantly increased from M2-like macrophages when compared to M1-like or non-activated M0 macrophages (Figure 4c). Given that M2-like macrophages exhibited fragmented mitochondrial networks and enhanced mitochondrial transfer rates, we hypothesized that smaller mitochondrial fragments might be transferred more readily than larger networks. To test this hypothesis, we directly manipulated mitochondrial morphology by modulating a key regulator of mitochondrial fission, DRP1 (Fonseca et al., 2019). Macrophages transduced with DRP1-shRNA containing lentivirus exhibited hyper-fused mitochondrial networks (Figure 4d and e) and exhibited decreased mitochondrial transfer (Figure 4f). Together these findings reveal that macrophage activation alters mitochondrial dynamics, and that altering mitochondrial dynamics directly affects mitochondrial transfer rates. Finally, to determine whether the functionality of transferred mitochondria differ between macrophage subtypes, we evaluated the membrane potential of transferred mitochondria, and found that transferred mitochondria from M1-like and M2-like macrophages were similarly depolarized (Figure 4—figure supplement 1e), as to what we observed with M0 macrophages (Figure 2b). Taken together, these results suggest that pro-tumorigenic M2-like macrophages exhibit increased mitochondrial fragmentation, promoting mitochondrial transfer to cancer cells.

Figure 4. M2-like macrophages exhibit increased mitochondrial fragmentation and increased mitochondrial transfer to cancer cells.

(a) Representative images of mito-mEm+ macrophages that were non-stimulated (M0, left) or activated to become M1-like (middle) or M2-like (right). (b) Mitochondrial network analyses (MiNA) were used to determine number of mitochondrial fragments per cell (N=2 donors). (c) Macrophages were co-cultured with mito-RFP 231 cells for 24 hr and mitochondrial transfer was quantified with flow cytometry (N=4 donors). (d) Representative images of mito-mEm (green) macrophages in macrophages with control nt-shRNA KD and DRP1 KD. (e) q-RT-PCR of DRP1 knockdown (DRP1-KD) macrophages (N=3 donors). (f) Rates of mitochondrial transfer with control and DRP1-knockdown macrophages (N=3 donors). For all panels, individual donors are indicated as shades of gray with each cell as a data point, error bars represent SEM and scale bars are 10 µm. Two-way ANOVA (b, c), unpaired t-test (e, f), ***p<0.001; ****p<0.0001.

Figure 4.

Figure 4—figure supplement 1. M2-like macrophages exhibit increased mitochondrial transfer to cancer cells.

Figure 4—figure supplement 1.

(a) Macrophages were activated with IFN-γ (M1 activation; left) or IL-4/IL-13 (M2 activation; right) for 48 hours and flow cytometry was used to determine expression of canonical M1 (CD86, left) and M2 (CD206, right) markers. Representative histograms shown. (b) Mitochondrial Network Analyses (MiNA) workflow with a representative input confocal image (left) and example of skeletonized mitochondrial network (right) to quantify number of branches per individual mitochondria, branch length, and number of junctions per individual mitochondrion. (c) Representative confocal image with a post-processed skeletonized version of network overlaid. (d) Percent mitochondrial fragmentation in M0, M1-like, and M2-like macrophages (N=2 donors). Two-way ANOVA, ****p<0.0001. (e) Representative confocal images of mito-RFP 231 cells co-cultured with mito-mEm M1-like (left) or M2-like (right) macrophages and stained with MitoTracker Deep Red (MTDR, yellow) and LysoTracker (LT, Teal). 100% of transferred mitochondria (green, arrowhead) from M1-like and M2-like macrophages are MTDR-negative. 63.6% (from M1-like) and 48% (from M2-like) of transferred mitochondria do not co-localize with LT (For M1-like MTDR and LT staining, N=15 cells, 2 donors; for M2-like MTDR staining, N=24 cells, 2 donors; for M2 LT staining, N=17 cells, 2 donors). For all panels, individual donors are indicated as shades of gray, error bars represent SEM and scale bars are 10 μm.
Figure 4—figure supplement 2. Macrophages transfer mitochondria to breast cancer patient-derived cells.

Figure 4—figure supplement 2.

(a) Representative images of the HCI-037 patient-derived xenograft organoid (PDxO) line in culture (top) or an embedded hanging drop co-culture with macrophages (bottom). (b) Schematic of experimental setup of PDxOs (gray)/mito-mEm macrophages (green) co-cultures. Co-cultures are plated in suspended drops of media (hanging drops) to allow for the formation of cell aggregates without adherence to a substrate. After 24 hr, the co-cultured cells are embedded into a matrix (Matrigel) and cultured for 72 hr before analysis with flow cytometry. (c) Representative image of a FACS-isolated PDxO cell containing macrophage mitochondria (green, arrowhead) that are MTDR-negative. (d) Top row: Representative flow cytometry plot of PDxO monocultured cells used as the experimental control when quantifying mitochondrial transfer. Middle row: PDxO cells co-cultured with mito-mEm-expressing M0 macrophages. Bottom row: PDxO cells co-cultured with mito-mEM expressing M2-like macrophages. PDxO lines used for co-culture are indicated at the top of the corresponding panels. Scale bars are 10 μm. (e), Rate of mitochondrial transfer to HCI-037 (left 3 columns) or HCI-038 (right 3 columns) PDxO cells from M0 or M2 macrophages (each dot is one replicate, N=4 donors). Two-way ANOVA, **p<0.01; ***p<0.001; ****p<0.0001.

To assess whether mitochondrial transfer also occurs in a clinically relevant cancer model, we used three-dimensional stable organoid cultures generated from patient-derived xenografts (PDxOs) (Guillen et al., 2021). We examined organoids from a recurrent primary breast tumor (HCI-037) and a bone metastasis (HCI-038) derived from the same breast cancer patient. PDxOs grown in 3D (Figure 4—figure supplement 2, top) were dissociated, combined with mito-mEm+ macrophages (Figure 4—figure supplement 2a, bottom), and then embedded in Matrigel (experimental scheme in Figure 4—figure supplement 2b). After 72 hr, mitochondrial transfer was assayed by live imaging (Figure 4—figure supplement 2c) and quantified with flow cytometry (Figure 4—figure supplement 2d, e, ). Mitochondrial transfer was observed from macrophages to both HCI-037 and HCI-038 PDxO cells (Figure 4—figure supplement 2e), although intriguingly, M2-like macrophages preferentially transferred mitochondria to the bone metastasis PDxO cells (HCI-038), whereas M0 and M2-like macrophages transferred mitochondria to primary breast tumor PDxO cells (HCI-037) at the same rate. In all cases, transferred macrophage mitochondria lacked membrane potential (Figure 4—figure supplement 2c), consistent with our results in 231 recipient cells.

Cancer cells with macrophage mitochondria exhibit increased proliferation in vivo

Next, to better model a tumor environment, we examined macrophage mitochondrial transfer to cancer cells in two separate in vivo models of metastatic breast cancer. We first injected E0771 murine adenocarcinoma cells expressing mito-mEm into wildtype C57BL/6J mice that had received lethal irradiation with subsequent bone marrow reconstitution from mito::mKate2 mice (mito:mKate2→WT), restricting mKate2 expression to immune cells (experimental schematic in Figure 5—figure supplement 1a). We found that in vivo mitochondrial transfer occurred at a rate of 4.8%, compared to control transplantation studies at 0.46% (Figure 5a). We also performed experiments in mice that restrict GFP-labeled macrophage mitochondria to the myeloid lineage by using the LysM-Cre transgenic mouse crossed to the lox-stop-lox-MitoTag mouse (experimental schematic Figure 5b, see methods for more details). We injected E0771 cells expressing mito-RFP into these mice with GFP-labeled macrophage mitochondria and observed E0771 cells containing macrophage mitochondria using immunohistochemistry approaches of tumor sections (Figure 5c; Figure 5—figure supplement 1b). Using similar cell proliferation analyses as previously described (Figure 1e), we also observed that recipient tumor cells exhibited enhanced proliferative capacity compared to the tumor cells that did not receive transfer (Figure 5d; Figure 5—figure supplement 1c). These results show that mammary adenocarcinoma cells with macrophage mitochondria exhibit increased proliferation in vivo.

Figure 5. Macrophage mitochondrial transfer promotes tumor cell proliferation in vivo.

(a) Quantification of E0771 mammary adenocarcinoma cells from in vivo tumors with mKate2+ mitochondria in bone marrow reconstitution experiments versus control mice. N=10 mice per condition. (b) Schematic representation of a second mouse model to quantify proliferation in cancer cells with macrophage mitochondria in vivo. Myeloid lineages were specifically labeled with mito-GFP by crossing a Loxp-Stop-Loxp-MitoTag-GFP mouse to a LysM-Cre mouse. E0771 cells expressing mito-RFP were injected into the mammary fat pad of mice with MitoTag-GFP expression in myeloid cells, and tumors were isolated and analyzed for direct observation of transfer through fluorescent microscopy (c) and Ki67/DNA to quantify proliferative index (d). (c) Representative immunofluorescence image of E0771 tumor cell expressing mito-RFP (magenta) containing GFP+ macrophage mitochondria (arrowheads) from mice in which GFP+ mitochondria are restricted to the myeloid lineage (‘LysM-Cre’). (d) Cell cycle analysis of E0771 in vivo tumor cells with and without GFP+ macrophage mitochondria in ‘LysM-Cre’ model in which GFP+ mitochondria are restricted to the myeloid lineage. N=3 mice. (e) Working model for macrophage mitochondrial transfer to breast cancer cells. For all panels, individual donors are indicated as shades of gray with each cell as a data point, error bars represent SEM and scale bars are 10 µm. Welch’s t- test (a), two-way ANOVA (d), **p<0.01; ****p<0.0001.

Figure 5.

Figure 5—figure supplement 1. Murine mammary adenocarcinoma cells with macrophage mitochondria exhibit increased cell proliferation in vivo.

Figure 5—figure supplement 1.

(a) Schematic representation of mouse model to quantify macrophage mitochondrial transfer. Bone marrow from either mito::mKate2 or wildtype mice are transplanted into gamma-irradiated mouse hosts. Once grafted, E0771 cells expressing mito-mEm are injected into the mammary fat pad of these mice, and tumors were isolated and analyzed for mitochondrial transfer by flow cytometry. (b) Schematic representation of a second mouse model to quantify proliferation in cancer cells with macrophage mitochondria in vivo. Myeloid lineages were specifically labeled with mito-GFP by crossing a Loxp-Stop-Loxp-MitoTag-GFP mouse to a LysM-Cre mouse. (c) Gating strategy for Ki67/DNA analysis for E0771 tumors.
Figure 5—figure supplement 2. Predicted increase in population size due to transferred mitochondria as a function of number of population doublings.

Figure 5—figure supplement 2.

Model results are presented as the ratio of mP, the mass of the population receiving macrophage mitochondria to mB, the mass of the population with baseline growth rate. The initial fraction of cells with transferred mitochondria and the fraction of the population receiving mitochondria, f, over any cell division cycle is assumed to be 5%. 50% of cells lose mitochondria at division. The population was initially seeded with 100 cells and an even distribution of mass between m0 and 2 m0, the baseline initial mass.

Finally, to determine the impact of macrophage mitochondrial transfer on population growth over time, we derived a relationship between overall growth of the cell population and the fraction of cells with macrophage mitochondria that experience an increase in growth rate (Figure 5—figure supplement 2). We used this analysis to predict the increase in population size due to transferred mitochondria as a function of the number of population doublings. The fraction of the population receiving mitochondria was assumed to be 5% based on our in vivo studies (Figure 5a), with the tumor cell population exhibiting a 15% increase in baseline growth rate due to transferred mitochondria based on QPI growth rate measurements (Figure 1f). We also assumed that half of the population loses transferred mitochondria, and the associated growth increase, with every division given that our QPI measurements indicated that typically only one of the daughter cells inherit the parent’s exogenous macrophage mitochondria (Figure 1—figure supplement 3a–c). By 20 divisions, with a 15% increase in growth rate (brown line), even with only 5% of the cancer cell population with macrophage mitochondria at any given time, the model already predicts a 15% increase in population size compared to baseline population rates (comparing the brown line to the blue dotted line). These results highlight the significance of macrophage mitochondrial transfer on the growth of a cell population over time. Taken together, our work supports a model (Figure 5f) whereby M2-like macrophages exhibit fragmented mitochondria leading to increased mitochondrial transfer. In the recipient cancer cell, transferred mitochondria are long-lived, depolarized, and accumulate ROS, leading to increased ERK activity and subsequent cancer cell proliferation.

Discussion

Lateral mitochondrial transfer is a relatively young and rapidly evolving field. Previously literature had shown that healthy mitochondria are transferred, enhancing recipient cell viability by increasing ATP production and stimulating metabolic processes. Our observations, however, suggest that transferred mitochondria promote tumor cell proliferation as a byproduct of their potential dysfunctionality. This model raises several fascinating questions, including when and how transferred mitochondria become depolarized and accumulate ROS, where the ROS is generated in the recipient cell, and why depolarized mitochondria are not repaired or degraded in the recipient cell, given that 231 cells are capable of performing mitophagy (Biel and Rao, 2018). Impaired mitophagy and enhanced mitochondrial dysfunction are hallmarks of age (Chen et al., 2020), yet little is known about how age-related mitochondrial dysfunction influences mitochondrial transfer. Interestingly, instead of degrading dysfunctional mitochondria through mitophagy, neurons in an Alzheimer’s disease mouse model have been shown to transfer dysfunctional mitochondria to neighboring astrocytes (Lampinen et al., 2022), which contributes to neuronal mitochondrial homeostasis. Given that age is the greatest known risk factor of Alzheimer’s disease, and most cancers are also age-related, these data collectively warrant broader investigations into how age-associated mitochondrial dysfunction contributes to mitochondrial transfer and how this form of communication may have specific influences on distinct diseased states.

Cellular stress occurs throughout biological systems, and cells have evolved a myriad of mechanisms to cope with disadvantageous cellular conditions, including mitochondrial stress (Ma et al., 2020). Our results suggest that transferred mitochondria are a source for downstream signal activation through a ROS-ERK-mediated mechanism. The origin of ROS generation in recipient cells is still unclear, and how ROS locally accumulate at macrophage mitochondria is an open question. It is possible that ROS are generated by the transferred mitochondria themselves, as previous reports have shown that mitochondria with reduced membrane potential can generate ROS (Feng et al., 2022; Franco-Iborra et al., 2018; Nakai et al., 2003). However, there are multiple mechanisms for ROS production (Zhao et al., 2019), and it is possible that the ROS are generated elsewhere in the cell and accumulating at transferred mitochondria. A previous report showed that the endoplasmic reticulum can produce ROS in the presence of dysfunctional mitochondria (Leadsham et al., 2013), suggesting another possible explanation. The questions of how ROS is generated, and how ROS can be spatially restricted to a specific subcompartment of the cell are exciting avenues of investigation and much further study. Although high levels of ROS are cytotoxic to cells (Stadtman and Levine, 2000; Fruhwirth and Hermetter, 2008; Auten et al., 2002), physiological levels of ROS are known second messenger molecules stimulating various pro-survival signaling cascades (Schieber and Chandel, 2014; Brillo et al., 2021). Additionally, a modest increase of mitochondrial-derived ROS has been shown to exhibit protective mechanisms through mitohormesis (Crewe et al., 2021; Ristow and Schmeisser, 2014), a process in which cellular defense mechanisms are stimulated by sub-lethal stress levels, protecting cells to withstand a secondary exposure. Mitochondrial transfer has been shown to promote resistance to subsequent chemotherapeutic treatments in healthy neurons (English et al., 2020) and tumor cells (Wang et al., 2018; Boukelmoune et al., 2018), however the mechanism of this resistance is unclear. It is possible that mitochondrial transfer mediates this protective response through mitohormesis, promoting longevity and proliferation of the recipient cancer cells. More studies are required to connect mitochondrial transfer, sub-lethal cellular stress, and resistance to chemotherapeutic treatments in disease progression and tissue homeostasis.

The role of mitochondrial transfer has been largely studied in recipient cells. There remains a dearth of information describing how donor cells regulate mitochondrial transfer. Although intercellular mitochondrial transport has been implicated in the process of mitochondrial transfer (Boukelmoune et al., 2018; Ahmad et al., 2014), we show that macrophage differentiation directly affects mitochondrial transfer through changes in their mitochondrial morphology. The relationship between macrophage differentiation and metabolism has been partially defined, with anti-tumor-like (M1-like) macrophages exhibiting more glycolytic metabolism, and pro-tumor-like (M2-like) macrophages upregulating oxidative phosphorylation (Van den Bossche et al., 2017; Mortezaee and Majidpoor, 2022). But how mitochondrial morphology regulates metabolism is less understood. Studies have indicated that mitochondrial fusion supports increases oxidative phosphorylation in fibroblasts (Yao et al., 2019), however other studies have shown that increasing mitochondrial fission upregulates oxidative phosphorylation in hepatocytes (Zhou et al., 2022). Thus, the correlation between mitochondrial morphology and cellular metabolic status is unclear, and these differences are likely due to different cell types and environmental conditions. While how the metabolic status of donor cells influences mitochondria is still unknown, our results support the hypothesis that pro-tumorigenic M2-like macrophage activation promotes mitochondrial fragmentation, and that mitochondrial fragmentation directly promotes mitochondrial transfer.

Our findings are consistent with several studies describing a metastatic advantage in cancer cells that receive exogenous mitochondria (Zampieri et al., 2021; van der Merwe et al., 2021; Dong et al., 2017; Tan et al., 2015). However, the mechanism underlying this behavior is unexpected. Studies examining mitochondrial transfer have typically used recipient cells with damaged or non-functional mitochondria, and the fate and function of donated mitochondria are rarely followed in recipient cells. Furthermore, it was largely unclear how transferred mitochondria can affect the behavior of recipient cells with functioning endogenous mitochondrial networks, particularly if the donated mitochondria only account for a small fraction of the total mitochondrial network in the recipient cell. Our work detailing how transferred mitochondria can activate downstream signaling pathways in response to ROS provides an explanation for how a relatively small amount of transferred mitochondria can generate a sustained behavioral response in recipient cells.

Materials and methods

Cell culture of cell lines and peripheral blood mononuclear cells (PBMCs)

Human cell lines MDA-MB-231 (HTB-26), MDA-MB-468 (HTB-132), A375 (CRL-1619), THP-1 (TIB-202), MCF10A (CRL-10317), and the murine cell lines E0771 (CRL-3461) were directly purchased from American Type Culture Collection and cultured according to their recommendations. Cell lines are authenticated through STR profiling, and all cultured cell lines are subjected to mycoplasma testing every 6 months using the Universal Mycoplasma Detection Kit (30–1012 K, ATCC). Base medias used were DMEM, high glucose (11965118, ThermoFisher), RPMI (11875119, ThermoFisher) and 10% heat-inactivated fetal bovine serum (FBS; F4135, ThermoFisher). All cell lines were kept in culture for no more than 25 passages total.

Genetic modification of PBMCs and differentiation into macrophages

PBMCs were isolated from leukocyte filters obtained from de-identified human blood donors (ARUP Blood Services). CD14 +monocytes were isolated from buffy coats and genetically modified with lentiviral vectors in the presence of virus-like particles packaging Vpx (to overcome restriction in myeloid cells) as previously described (Johnson et al., 2020; Greiner et al., 2022). Briefly, freshly harvested CD14 +monocytes were plated at a density of 4–5 M cells per 10 cm plate in ‘macrophage culture media’ containing: RPMI (11875119, ThermoFisher), 10% FBS (26140079, Thermo Fisher), 0.5% penicillin/streptomycin (P/S; P4333, Thermo Fisher), 10 mM HEPES (15630080, ThermoFisher), 0.1% 2-Mercaptoethanol (21985023, Thermo Fisher), recombinant human GM-CSF at 20 ng/ml (300–03, Peprotech) with the addition of polybrene (1 μg/ml), and supernatant containing Vpx particles (0.5 mL per 4 M cells) to facilitate viral transduction. Thirty min after plating, 100–200 µL of concentrated lentiviral stock was added to the plated monocytes. 50% of the media was replaced on day 2 and a full media replacement occurred on day 4. Macrophages were used for experiments starting on day 6 or 7 after harvest of PBMCs unless otherwise noted.

Distinction of biological and technical replicates

Each human blood donor (referred to as ‘donors’ or ‘experiments’) is a biological replicate. Multiple samples from each donors run in parallel are defined as technical replicates (typically in triplicate for each biological replicate).

Generation of mito-FP and FP-TOMM20 stable cell lines

We generated a modified pLKO.1 plasmid backbone with an accessible multiple cloning site (pLKO.1_MCS) for generation of fluorescent reporters. For mito-FP expression, we cloned the cytochrome oxidase subunit VIII mitochondrial targeting sequence and tagged it to mEmerald (referred to as mito-mEm) or tagRFPt (referred to as mito-RFP) and introduced these into the pLKO.1_MCS backbone in order to generate lentiviruses. pLKO.1 mito-mEmerald and pLKO.1 mito-TagRFP-T are available on Addgene (#174542 and 174543, respectively). For FP-TOMM20 expression, inserts containing the sequence of either mEmerald (mEmerald-TOMM20) or mcherry (mCherry-TOMM20) fused to TOMM20 and cloned into the pLKO.1 backbone and used to generate lentiviruses. Stable lines were generated through lentiviral transduction. For transduction, approximately 50,000 cells were plated into one well of a 6-well plate directly into the appropriate lentivirus supernatant diluted 1:5 in DMEM complete media with a final concentration of 10 µg/mL polybrene (TR-1003-G, Sigma). After 48–72 hr, cells were expanded, and multiclonal populations were flow sorted for appropriate levels of fluorescent expression. All other transgenic cell lines were generated as outlined in subsequent sections.

mEmerald-TOMM20-N-10 (Addgene plasmid # 54282) and mCherry-TOMM20-N-10 (Addgene plasmid # 55146) were a gift from Michael Davidson.

Lentivirus production

pLKO.1_MCS plasmids containing the appropriate transgene were used to generate lentivirus as outlined in Johnson et al., 2020. Briefly, 293 FT cells in 15 cm plates were transfected with PEI-max (24765, Polysciences) and plasmids for pCMV-VSV-G, psPax2, and transgene cassettes. The following day, cells were washed and cells were grown for an additional 36 hr in fresh media. Supernatants were harvested, passed through 0.45 μm filters, and either used fresh or concentrated by ultracentrifugation as previously described (Johnson et al., 2020). Lentiviral supernatants were used to transduce cell lines as outlined in ‘generation of mito-FP’ section unless otherwise noted.

Flow cytometry

The following flow cytometry machines were used: a BD FACS Aria (equipped with 4 Lasers: 405, 488, 561, 640) referred to as Aria, or a BD LSR Fortessa (5 Lasers: UV, 405, 488, 561, 640) referred to as the Fortessa. Technical details per experiment type are listed below.

Stable line generation

Cells were enzymatically dissociated using trypsin-EDTA (25200056, ThermoFisher) and resuspended in buffer consisting of 0.5% Bovine Serum Albumin (BSA; Sigma, A9418) in DPBS (14190250, ThermoFisher). Cells were sorted according to fluorescent intensity on the Aria and collected in the appropriate media containing 0.5% P/S.

Mitochondrial transfer quantification

For MDA-MB-231 and MCF10A cell lines: cells were enzymatically dissociated using trypsin-EDTA and stained as follows: cells were resuspended in ‘staining buffer’ (DPBS + 2% FBS) containing a human antibody against CD11b conjugated to the fluorophore Brilliant Violet 711 (BV711-CD11b; macrophage marker; Biolegend, 301344) at a 1:20–40 dilution. After a 30 min incubation on ice, cells were washed and resuspended in cold DPBS for analysis on the Fortessa. The background level of mEmerald fluorescence was set at 0.2% based on a fully stained co-culture control where macrophages were not transduced with mito-mEmerald. This gate was defined by FACS-isolating co-cultures of mito-RFP MDA-MB-231/mito-mEm macrophages and determining a gate that accurately isolated MDA-MB-231 cells containing macrophage mitochondria. We found that the cancer cell population with the highest mEm signal were cancer/macrophage fusions, and we therefore removed this population from downstream analysis. Setting the gate to 0.2% predominantly led to isolation of cancer cells with fragments of macrophage mitochondria, as visualized by microscopy.

Mitochondrial transfer quantification of PDxO containing co-cultures

Hanging drop co-cultures suspended in Growth Factor Reduced Matrigel (354230, Corning) were pooled and dissociated using a solution of Dispase II (50 U/mL; 17105041, Fisher Scientific) followed by TrypLE Express (12605010, Thermo Fisher). Cells were then incubated in TrueStain FcX (422301, ThermoFisher) at 1:33 dilution with staining buffer for 10 min at room temperature. Primary human antibodies against CD326 conjugated to PE (PE-EpCam; PDxO marker; 369806, Biolegend) and BV711-CD11b were added at 1:20 and 1:40, respectively. After 30 min on ice, cells were washed and resuspended in cold DPBS for analysis on the Fortessa. The background level of mEmerald fluorescence in the ‘transfer gate’ was set at 0.2% based on a fully stained monoculture control.

Quantification of Ki67 and DNA content

Co-cultures were enzymatically dissociated with trypsin-EDTA and incubated in staining buffer containing anti-human BV711-CD11b at 1:40 for 30 min on ice. Cells were then fixed and stained using the eBioscience Foxp3/Transcription Factor Staining Buffer Set (00-5523-00, ThermoFisher) according to manufacturer’s instructions. Cell were stained with an APC conjugated Ki67 antibody (APC-Ki67; 17-5699-42, ThermoFisher) at 1:20 for 30 min followed by a 3 µM DAPI (D9542, Sigma) solution for 10 min. Cells were resuspended in cold DPBS for analysis on the Fortessa. The background level of mEmerald fluorescence in the ‘transfer gate’ was set at 0–0.2% based on a fully stained co-culture control where macrophages were not transduced with mito-mEmerald.

Single-cell RNA-seq

Mito-mEm macrophages were cocultured with mito-RFP 231 cells for 24 hr. Two populations were FACS-isolated: (1) Mito-RFP 231 cells containing mito-mEm macrophage mitochondria; (2) mito-RFP 231 cells not containing mito-mEm macrophage mitochondria. From FACS-isolated populations, a cDNA library was generated using the 10 X genomics Single Cell 3’ Gene Expression Library V3 and amplified according to the manufacturer’s protocol. The resulting libraries were sequenced on a NovaSeq 6000 resulting in approximately 100 K mean reads per cell. The raw sequencing data were processed using CellRanger 3.02 (https://support.10xgenomics.com/) to generate FASTQ files, aligned to GRCh38 (Ensemble 93), and a gene expression matrix for individual cells based on the unique molecular indices was generated. The resultant filtered gene-cell barcode matrix was imported into SEURAT version 4 (Hao et al., 2020) with R studio version 1.3.1093 and R version 4.03. We first performed quality control by determining the mean and standard deviation of genes per cell and filtered out all cells that were more than 1.5 standard deviations away from the mean. The reads were then scaled and normalized using SEURAT ‘sctransform’ function (Hafemeister and Satija, 2019). Using the normalized data, we determined differential gene expression in the MDA-MB-231 population that received macrophage mitochondria compared to those that did not, using a non-parametric Wilcoxon rank sum test with the SEURAT ‘FindMarkers’ function. Lastly, the differential expression data were exported from R and pathway enrichment analysis was performed using Qiagen’s Ingenuity Pathway Analysis software (Krämer et al., 2014). Single-cell RNA-sequencing data are available with GEO accession number GSE181410. The analysis code for single-cell RNA-sequencing analysis is available on GitHub (https://github.com/rohjohnson-lab/kidwell_casalini_2021; RRID:SCR_002630 (version number 1)).

Trans-well experiments

Approximately 40,000 mito-RFP MDA-MB-231 and 80,000 mito-mEm macrophages were plated in trans-wells (3401, Corning) under the conditions listed in Figure 1—figure supplement 1e–h. Cells were analyzed after 24 hr with flow cytometry as indicated in ‘mitochondrial transfer quantification’ section.

Live cell imaging of co-cultures with cell-permeable dyes

Imaging was performed using either a Zeiss LSM 880 with AiryScan technology (Carl Zeiss, Germany) and a 63 x/1.4 NA oil objective or a Leica Yokogawa CSU-W1 spinning disc confocal microscope with a Leica Plan-Apochromat 63 x/1.4 NA oil objective and iXon Life 888 EMCCD camera. Images taken on the LSM 880 were acquired using the AiryScan Fast mode. For all live imaging, cells were maintained at 37 °C, 5% CO2 with an on-stage incubator.

MDA-MB-231 cells and primary macrophages stably expressing the appropriate transgenes were mixed in a 1:2 ratio and plated at an approximate density of 300,000 cells directly onto 35 mm glass bottom dishes (FD35-100, World Precision Instruments) for all live imaging experiments unless otherwise noted. Duration of co-culture is indicated in main text or figure legend.

For detection of nuclear and mitochondrial DNA, Hoechst 33342 (B2261, Sigma) was diluted into the culture media to a final concentration of 5 μg/mL. After 10 min at 37 °C, cells were washed, and complete media was replaced before imaging.

For detection of mitochondrial membrane potential with MitoTracker Deep Red (MTDR; M22426, ThermoFisher), MTDR was diluted into serum-free DMEM media (11965118, ThermoFisher) at a final concentration of 25 nM and incubated at 37 °C for 30 min. Following incubation, cells were washed with warm PBS, and warmed complete media was replaced before imaging.

For detection of mitochondrial membrane potential with Tetramethylrhodamine, Methyl Ester, Perchlorate (TMRM; T668, ThermoFisher), TMRM was diluted into serum-free DMEM media at a final concentration of 100 nM and incubated at 37 °C for 30 min. Following incubation, cells were washed with warm PBS, and warmed complete media was replaced before imaging.

For detection of lysosomes and acidic vesicles, LysoTracker Blue (L7525, ThermoFisher) was diluted to a final concentration of 75 nM in serum-free DMEM media and incubated at 37 °C for 30 min. Following incubation, cells were washed with warm PBS and warmed complete media was replaced before imaging.

For detection of plasma/vesicular membranes, MemBrite 640/660 (Biotium, 30097) was used at a final concentration of 1:1000 and stained according to manufacturer’s instructions. To preferentially label intracellular membrane compartments, cells were allowed to rest for 45 min after Membrite 640/660 staining before imaging, as indicated in the manufacturer’s instructions.

For detection of ROS, Carboxy-H2DCFDA (C400, ThermoFisher) was diluted to 5 μM into warmed HBSS (14025092, ThermoFisher) and incubated at 37 °C for 15–30 min. After incubation, cells were washed with HBSS and warmed complete media was replaced before imaging.

Live imaging of sorted recipient cells

MDA-MB-231 cells were harvested and stained as indicated in ‘mitochondrial transfer’ section of flow cytometry methods. Cells were sorted on the Aria directly into media containing 0.5% P/S. Sorted cells were plated directly onto imaging dishes coated with CellTak (354240, Corning) and allowed to attach at 37 °C for up to 4 hr before staining and live imaging.

Quantitative phase imaging (QPI)

Mito-RFP MDA-MB-231 cells and mito-mEm macrophages were seeded in a 1:2 ratio at a density between 90,000 and 120,000 cells directly onto imaging dishes 24 hr prior to the start of imaging. QPI images were acquired on Olympus IX83 inverted microscope (Olympus Corporation, Japan) with Phasics SID4 camera (Phasics, France) and Thorlabs 623 nm wavelength DC2200 LED (Thorlabs, USA). The microscope was operated in brightfield with Olympus UPLFLN 40 X objective and a 1.2 X magnifier in front of camera, giving ×48 magnification. Fluorescence images were acquired using X-Cite 120LED illumination (Excelitas technologies, USA) and an R1 Retiga camera (Cairn research Ltd, UK) with GFP (Olympus Corporation U-FBNA) and RFP (IDEX health & science, USA mCherry-B-000) filter cubes. Cells were maintained at 37 °C temperature, 5% CO2 and 90% humidity with an Okolab (Okolab, Italy) on-stage incubator on a Prior III Proscan microscope stage (Prior Scientific Instruments Ltd., UK). Automation was performed with MicroManager open-source microscopy software via MATLAB 2012b. QPI images of 40 positions per imaging set, four replicate (biological replicate) imaging sets total, were acquired every 15 min with fluorescence images acquired in an alternate subset of locations every 15 min for 48 hr to reduce phototoxicity.

QPI data analysis

QPI and fluorescent images were analyzed with MATLAB 2019a. Cell phase shift images were background corrected using sixth order polynomial surface fitting, and converted to dry mass (m) map, using, m=1αϕλdA, where λ, is the wavelength of source light = 0.623 µm, α, specific refractive increment = 0.185 µm3/pg, A, image pixel area = 0.36 µm2/pixel, and ϕ is the phase shift in fraction of a wavelength at each pixel. Cell dry mass maps were then segmented using a Sobel filter for edge detection and tracked over time (Crocker and Grier, 1996). Specific growth rate of each tracked cell was computed as the slope of a linear, least-squares best fit line to mass over time data normalized by cell average mass. Fluorescent mitochondria images were resized to match QPI images and overlaid with corresponding QPI image segmentation mask to measure the integrated fluorescence intensity of every cell, normalized by cell area. Macrophage mitochondria high frequency punctae signal in MDA-MB-2321 cells were separated from the high intensity, low spatial frequency of the macrophage mitochondria network fluorescence signal using the rolling ball filter in MATLAB. The size of the rolling ball was 4.8–9 μm, chosen to be just above the average size of mitochondrial punctae based on the quantity of mitochondria transferred and retained in the MDA-MB-231 cells. Cells with RFP signal 1.5 times more than the background were identified as MDA-MB-231 cells, and with mEmerald fluorescent signal double that of background as macrophages. MDA-MB-231 cell tracks were then binned based on the presence or absence of mEmerald +mitochondrial punctae, indicating transfer from macrophages. The specific growth rate of each cell was calculated as the slope of a least-squares linear fit to QPI mass vs time data divided by the average mass of the cell. The code for automated tracking of cell mass from QPI and fluorescence data and computing growth rates of the different groups of cells is available on GitHub (https://github.com/Zangle-Lab/Macrophage_tumor_mito_transfer, copy archived at ZangleLab, 2023).

Cytokinesis analysis

Cytokinesis rate was calculated by tracking cells manually to confirm division of cells in less than the maximum doubling time expected (40 hours). Cells leaving the imaging frame in less than 30 hr were omitted from the cytokinesis calculation.

Lineage analysis

The average specific growth rate of MDA-MB-231 parent and daughter cell was calculated by manually annotating mass versus time tracks from mass tracking based on the presence of mEmerald +punctae. The difference in growth of daughter cells that did or did not inherit mitochondria from mitochondria containing parents was observed by normalizing the mass of each daughter by its initial mass at birth.

ROS biosensor line generation, imaging, and quantification

MDA-MB-231 cells were transfected with the following plasmids: pLPCX mito-Grx1-roGFP2 (Gutscher et al., 2008) and pLPCX mito-roGFP2-Orp1 (Gutscher et al., 2009) (Addgene, plasmid #64977 and #64992, respectively) using the Polyplus-transfection jetPRIME DNA/siRNA transfection kit (55–131, Genesee Scientific) according to the manufacturer’s instructions. Cells were allowed to recover for 3–7 days and then sorted for expression. Cells were passaged every 3–5 days and sorted as needed to maintain a high percentage of expressing cells. Biosensor-expressing MDA-MB-231 lines were co-cultured with mito-RFP expressing macrophages for 24 or 48 hr and imaged on the Zeiss LSM 880. Cells were sequentially imaged (per z-plane) for the presence of transferred macrophage mitochondria (Ex. 561 nm, Em. BP 570–620nm +LP 645 nm) and the biosensor in its a reduced (Ex. 488 nm, Em. BP 420–480nm +BP 495–550 nm) and oxidized (Ex. 405 nm, Em. BP 420–480nm +BP 495–550 nm) form. Images were initially processed using Zen software (see image analysis section) and further analysis was performed using FIJI as indicated in Morgan et al., 2011. pLPCX mito Grx1-roGFP2 (Addgene plasmid # 64977) and pLPCX mito roGFP2-Orp1 (Addgene plasmid #64992) were a gift from Tobias Dick.

Mito-KillerRed line generation and imaging

To generate 3xHA-killerred-OMP25, a plasmid containing 3xHA-EGFP-OMP25 (Chen et al., 2016) was used as a template and the sequence of KillerRed replaced EGFP. The entire transgene was then cloned into the pLKO.1_MCS backbone. pLKO.1 3xHA-KillerRed-OMP25 is available on Addgene (#174544). MDA-MB-231 cells were transduced with lentiviral supernant that packaged the 3xHA-killerred-OMP25 transgene, allowed to recover and were cell sorted to select for the appropriate level of fluorescent expression. Cells expressing both mito-mEm and mito-KillerRed were generated in parallel to confirm the correct localization of the mito-KillerRed (data not shown).

pMXs-3XHA-EGFP-OMP25 was a gift from David Sabatini (Addgene plasmid #83356).

For generation of mt-ROS with the mito-KillerRed cell line

MDA-MB-231 mito-KillerRed-expressing cells were labeled with Carboxy-H2DCFDA as described above. Using a Leica Yokogawa CSU-W1 spinning disc confocal microscope equipped with a 2D-VisiFRAP Galvo System Multi-Point FRAP/Photoactivation module, MDA-MB-231 mito-KillerRed-expressing cells were imaged at 488 nm (for DCFDA detection) and 561 nm (for mito-KillerRed detection) at a time interval of 2 seconds. After 2 frames, a~2µm x 2µm region of interest (ROI) of mito-KillerRed was photobleached using a 561 laser (100% laser power, 5ms, 1 cycle), and continuous imaging at 488 nm and 561 nm allowed for DCFDA quantification and mito-KillerRed photobleaching, respectively.

To quantify cell division upon ROS production

Cells were stained with 5 μg/mL Hoescht 33342 as described above to visualize nuclei. Multiple stage positions were established such that control experiments, in which a cytoplasmic ROI without mito-KillerRed expression that was photobleached using identical parameters, as well as a no-photobleaching control, could be imaged simultaneously with experimental photobleached cells. Approximately 8–10 cells of each category – photobleached in mito-KillerRed-expressing regions, photobleached in control cytoplasmic non-expressing regions, or not photobleached – were imaged by acquiring Z-stacks (1 µm step size) every 15 min for 18 hr. Cell division was quantified by visualizing nuclear division with FIJI software.

ERK-KTR generation

MDA-MB-231 cells were transduced with lentiviral supernant that was packaged using either pLentiPGK Blast DEST ERKKTRmRuby2 or pLentiPGK Puro DEST ERKKTRClover plasmids (Kudo et al., 2018) as outlined in ‘generation of mito-FP’ section. Cells were allowed to recover post-infection, sorted for fluorescent expression, and maintained as stable cell lines.

pLentiPGK Blast DEST ERKKTRmRuby2 (Addgene plasmid # 90231) and pLentiPGK Puro DEST ERKKTRClover (Addgene plasmid # 90227) were a gift from Markus Covert.

ERK-KTR-mClover and mito-KillerRed generation and imaging

A stable MDA-MB-231 line expressing mito-KillerRed was transduced with lentivirus that was packaged using a pLentiPGK Puro DEST ERKKTRClover plasmid. Cells were sorted for expression of both mito-KillerRed and ERK-KTR-mClover and maintained as a stable line.

For mt-ROS generation and ERK-KTR imaging

MDA-MB-231 cells expressing mito-KillerRed and ERK-KTR-mClover were stained with 5 μg/mL Hoescht 33342 as described above to visualize nuclei. Using a Leica Yokogawa CSU-W1 spinning disc confocal microscope equipped with a 2D-VisiFRAP Galvo System Multi-Point FRAP/Photoactivation module, MDA-MB-231 cells expressing mito-KillerRed and ERK-KTR-mClover were imaged every 1 minute with 561 nm (for mito-KillerRed) and 488 nm (for ERK-KTR-mClover) and 405 nm (for nuclei) lasers. A~2 µm x 2 µm ROI of KillerRed + mitochondria was photobleached using a 561 laser (100% laser power, 5ms, 1 cycle), and continuous imaging at 488 nm and 561 nm allowed for visualization of ERK-KTR-mClover translocation and mito-KillerRed photobleaching, respectively. Multiple stage positions were set such that control experiments, in which a cytoplasmic region without mito-KillerRed expression that was photobleached using identical parameters, could be imaged simultaneously with experimental photobleached cells.

ERK-KTR quantification with FIJI

ERK-KTR-mClover translocation was quantified every 10 minutes by taking maximum projections of Z-planes only encompassing the cell nucleus. Using FIJI software, a ROI was drawn in the nucleus guided by the Hoescht staining, and the MFI of ERK-KTR-mClover was quantified in this region. The same ROI was moved outside of the nucleus to a cytoplasmic region devoid of mitochondria, and the MFI of ERK-KTR-mClover was quantified. This analysis was performed for each timepoint after photobleaching. The values were then used to calculate a cytoplasmic:nuclear ratio at each time point, and normalized to 1 at time point zero.

Quantification of ERK-KTR using the Amnis ImageStream

To quantify translocation of the ERK-KTR-mRuby we used the Amnis Imagestream mk II with ISX software (version 201.1.0.725). Mito-mEm macrophages were co-cultured with ERK-KTR-mRuby+MDA MB-231 cells for 24 hr. Samples were prepared as indicated in ‘quantification of Ki67 and DNA content’ section with the exception that we did not stain for intracellular markers. Images were captured with the 40 x objective and sample collect flow was set to low, as this allows for higher image resolution. Using Image Data Exploration and Analyses Software (IDEAS; version 6), we quantified translocation using two metrics: (1) the IDEAS translocation Wizard and (2) custom-generated program to detect cytoplasmic (cyto) and nuclear (nuc) ERK-KTR mean fluorescent intensities (MFI) to calculate a cyto:nuc ratio as indicated in Figure 3—figure supplements 1 and 2. The translocation wizard is a pre-built program made to detect the nuclear translocation of a probe. It does this by making a pixel-by-pixel correlation between the probe of interest (ERK-KTR) and the nuclear image (DAPI). The program gives each cell a score indicating how similar the two fluorescent images are. A high score suggests the images are similar (more nuclear translocation) and a low score suggests that the images are less similar (less nuclear translocation). We also quantified ERK-KTR translocation by generating a custom masking strategy to quantify the mRuby MFI in the cytoplasm and nucleus using IDEAS software. To identify nuclear mRuby, we manually set a threshold of DAPI signal and reported the mRuby MFI of pixels within that threshold range. To quantify the cytoplasmic mRuby fraction we reported the mRuby MFI from outside the threshold. These values are then used to calculate a cyto:nuc ratio.

Drug treatments: ERKi, PMA and MitoTEMPO

SCH772984 (ERKi; 7101, SelleckChem) and Phorbol 12-myristate 13-acetate (PMA; S7791, Selleckchem) was dissolved in 100% DMSO to make 10 mM stock solutions and stored at –80 °C. No individual aliquot went through more than 2 freeze-thaw cycles. The stock solution was thawed and then diluted directly into complete media for a final concentration of 1 μM for ERKi and 100 nM (cancer cell treatment) or 162 nM (THP-1 differentiation) for PMA. For all ERKi experiments, co-cultures were treated at the time of plating and for a duration of 24 hr. For PMA treatment of cancer cells the cells were plated the day prior and were treated for 1 hr prior to harvest and analysis. THP-1 cells were differentiated for 24 hr in PMA prior to harvest. To quench mitochondrial ROS, MitoTEMPO (Cayman Chemical, 16621) was formulated at 200 mM in 100% DMSO and diluted directly into warm complete media for a final concentration of 100 μM. MDA-MB-468 cells were treated for the duration of 24 hours as described in 'Mitochondrial isolation and bath application', and cells were harvested for proliferative capacity analyses as previously in ‘Quantification of Ki67 and DNA content’. MitoTEMPO aliquots were stored at –20 °C, remained protected from light and never underwent a freeze-thaw cycle.

Macrophage activation and verification

For macrophage activation, macrophages were harvested and differentiated as indicated in ‘cell culture of PBMCs’ section. Between days 6–7 of differentiation, IFN-γ (3000–02, Peprotech, 20 ng/mL) for M1 activation or IL-4 +IL-13 (200–04, 200–13, Peprotech, 20 ng/mL) for M2 activation were added to culture media for 48 hr before experiments were conducted. To confirm M1 and M2 activation, macrophages were collected and stained for known surface markers for M1 (CD86; 62-0869-42, Thermofisher) and M2 (CD206; 321110, Biolegend) activation. Flow cytometry was performed on the Fortessa to observe changes in fluorescent intensities across M0, M1, and M2 macrophages populations (Figure 4—figure supplement 1a).

Immunofluorescence and analysis of mitochondrial morphology

Mito-mEm expressing macrophages were co-cultured with mito-RFP +MDA MB-231 cells for 24 hr and fixed with warm 4% PFA with 5% sucrose in 1 x DPBS for 20 min and permeabilized with 0.2% Triton X-100 in 1 x DPBS (9002-93-1, Sigma). Cells were stained with chicken α-GFP (AB13970, Abcam) and Rabbit α-RFP (AB62341, Abcam) antibodies at 1:500 and 1:1000, respectively. The following secondary antibodies were used: Alexa Fluor 488 AffiniPure Goat anti-Chicken (103-545-155, Jackson ImmunoResearch) and IgG (H+L) Cross-Adsorbed Goat anti-Rabbit Alexa Fluor 555 (A21428, Invitrogen) both at 1:500. Cells were subsequently stained with 1 μg/mL DAPI in DPBS for 10 min. Cells were then mounted with ProLong Diamond Antifade Mountant (P36965, ThermoFisher) and stored at 4 °C before imaging. Imaging was performed using the Zeiss LSM 880 using the AiryScan fast mode. AiryScan processed images (see image analysis section) were used to quantify mitochondrial morphologies with the FIJI plug-in, Mitochondrial Network Analyses (MiNA; Figure 4—figure supplement 1b–d). Pre-processing parameters: Manually select top and bottom of the cell of interest, exclude any space above and below the cell as this can introduce background noise. 3D project cell. Unmask sharp Radius (5), Mask Weight (0.6), Median 3D (0.5, 0.5, 0.5), Make binary (Otsu), Skeletonize, Analyze skeleton 2D/3D. A ‘mitochondrial fragment’ was defined as a mitochondrion with 0–1 branches, 0 junctions, and a length greater than 0 µm and a maximum length of 2 µm.

DRP1 knockdown

Monocytes were isolated as indicated in ‘cell culture of PBMCs’ section and transduced with lentiviruses to express mito-mEm and either non-target (nt) short hairpin (sh) RNA (SHC002, Sigma), or DRP1-shRNA (TRCN0000001097, Sigma; gene target HGNC ID 2973). All constructs were either produced or cloned into the pLKO.1 backbone.

rt-qPCR verification of genetic knockdown

RNA from nt-shRNA and DRP1-shRNA expressing macrophages were isolated from 3 independent macrophage donors. To isolate RNA, we used standard TRIzol/chloroform RNA isolation techniques. cDNA libraries were made using SuperScript III Reverse Transcriptase (18080093, ThermoFisher), according to manufacturer’s instructions. DRP1-knockdown was verified via qRT-PCR with Power SYBR Green Mast Mix (4368511, ThermoFisher). Primers were designed with NCBI primer design, commercially produced by Integrated DNA Technologies and tested for specificity with standard PCR. Primers were as follows; DRP1-F: AGAAAATGGGGTGGAAGCAGA, DRP1-R: AAGTGCCTCTGATGTTGCCA, GAPDH-F: AGCCACATCGCTCAGACA, GAPDH-R: ACATGTAAACCATGTAGTTGAGGT. Cycle Thresholds (CT) values were determined by averaging 3 technical replicates from 3 biological samples. Control ΔCT: expression was normalized to GAPDH by subtracting the DRP1 CT value of the nt-shRNA expressing macrophages from the GAPDH CT value of the same sample. Target gene, DRP1ΔCT: DRP1 CT values of the DRP1-shRNA expressing macrophages were subtracted from the GAPDH CT values of the same sample. The ΔΔCT values was calculated by subtracting DRP1ΔCT – control ΔCT. Normalized target gene expression was calculated (2-ΔΔCT) and used to determine % knockdown ((1–2-ΔΔCT)*100).

PDxO culture and co-culture with macrophages

PDxO cell lines HCI-037 and HCI-038 were generated and maintained as described in Guillen et al., 2021. Like MDA-MB-231 cells, these models are estrogen and progesterone receptor negative and HER2 negative (triple negative breast cancer). For co-culture with macrophages, mature PDxOs were dissociated from Growth Factor Reduced Matrigel with a Dispase II solution followed by treatment with TrypLE Express to generate a suspension of single cells. PDxO cells were then mixed with mito-mEm macrophages (differentiated for 7–9 days) in a 1:2 ratio at a density of 90,000 cells total per hanging drop culture. Macrophage media was used for hanging drops (for media components, see isolation of PBMCs section) and they were suspended from the lid of a tissue culture plate to allow for cell aggregation for 24 hr and then pooled and embedded into Growth Factor Reduced Matrigel. Embedded hanging drop cultures were then allowed to incubate for 72 hr and were then analyzed for mitochondrial transfer with flow cytometry (see flow cytometry section).

Mitochondrial isolation and bath application

For data represented in Figure 1g–j: 150–200x106 mito-mEm expressing THP-1 cells were pelleted by centrifugation for 5 min at 300 g. Pellets were resuspended in 2 mL of mitochondrial isolation buffer (70 mM sucrose, 220 mM D-mannitol, 2 mM HEPES, 1 x protease inhibitor, pH 7.4) and incubated on ice for 15–30 min. Suspended cells were dounce homogenized 100–150 times in a Potter-Elvehjem PTFE pestle and glass tube (Sigma, P7734). Cell homogenates were centrifuged at least twice (700 g for 10 min, 4 °C) to pellet and remove unwanted cellular material, until no pellet was observable – as many as 7 centrifugation cycles. Final supernatants were centrifuged at 20,000 g for 15 min at 4 °C to pellet isolated mitochondria. Mitochondrial pellets were suspended in ~250 μL of ice cold mitochondrial isolation buffer +protease inhibitor, and relative mitochondrial concentrations were determined via standard BCA protein concentration assay (ThermoFisher, 23225). 20–30 µg/mL of mitochondria were applied to pre-plated mito-RFP expressing MDA-MB-231 cells for 18–24 hours. After mitochondrial incubation cells were thoroughly washed to remove any un-internalized mitochondria and mitochondrial percent internalization was determined via flow cytometry and cells were FACS isolated with BD FACS Aria as described above under ‘Flow cytometry – Stable line generation’. FACS isolated cells were either imaged on the LSM880 Airy Scan Confocal as described in ‘Live cell imaging of co-cultures with cell-permeable dyes’, or plated for an additional 48 hr. After roughly two cell cycles, the cells were harvested and cell cycle analyses were conducted as described in ‘Quantification of Ki67 and DNA content’.

For data represented in Figures 2e–f ,3f: Mito-mEm expressing THP-1 monocytes were differentiated with 162 nM Phorbol 12-myristate 13-acetate (PMA - SelleckChem, #S7791) for 24 hr. Cells were trypsinized and washed with ice cold PBS and centrifuged at 300 g for 5 min. Cell pellets were suspended in 500–1000 μL mitochondrial isolation buffer +protease inhibitor and dounce homogenized as reported above. Final supernatants were centrifuged at 20,000 g for 15 min at 4 °C to pellet isolated mitochondria. Mitochondrial pellets were suspended in 110 μL of ice cold mitochondrial isolation buffer +protease inhibitor, and mitochondrial concentrations were determined via standard BCA (as above). Pre-plated MDA-MB-468 cells were bath applied with concentrations 3–5 µg/mL of exogenous mitochondria for 5–6 hr which was then removed to eliminate any un-internalized mitochondria. Twenty-four hr after initial mitochondrial addition, cells were either imaged on the LSM880 Airy Scan Confocal as described in ‘Live cell imaging of co-cultures with cell-permeable dyes’, treated with ERK inhibitor as described in ‘Drug treatments: ERKi, PMA and MitoTEMPO’ and harvested for cell cycle analyses were conducted as described in ‘Quantification of Ki67 and DNA content’. All drug treatments (ERK inhibitor and MitoTEMPO) were applied at the time of mitochondrial application and were maintained until harvest.

In vivo models

All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) at the University of Utah (protocol # 19–12001) and at the Cleveland Clinic (protocol #2179). In accordance to approved protocols, all animals were anesthetized appropriately to assure maximum comfort throughout the duration of procedures. When tumors were grown to approved volumes, mice were humanely euthanized with slow C02 gas exchange for 5 min. We calculated how many animals would be required for each experiment using G*Power3.1 – Based on our in vitro studies, we considered a 5% increase in mitochondrial transfer or a 5% increase in the percentage of cells in the G2/M phase of the cell cycle as statistically significant, with a 1% standard deviation, thus, we required a minimum of three animals per treatment group. With the variability in tumor growth, we injected at least five animals per treatment group such that we could ensure to complete studies with at least three animals. Regarding Figure 5a: Six-week-old C57BL/6J (The Jackson Laboratory, Stock #000664) and Tg(CAG-mKate2)1Poche/J (The Jackson Laboratory, mito::mKate2, stock #032188) female mice were purchased from the Jackson Laboratory as required and housed in the Cleveland Clinic Biological Research Unit Facility. Wild-type mice were treated with 11 Gy radiation split into two fractions. 2x106 bone marrow cells from mito:mKate2 or wild-type mice were retro-orbitally injected for reconstitution. Drinking water was supplemented with Sulfatrim (Pharmaceutical Associates, Inc) during the first 10 days, and mice were monitored for an additional 6 weeks. A total of 250,000 mito-mEm E0771 cells were mixed with 1:50 diluted Geltrex (ThermoFisher) and implanted to 4th mammary pad in 100 μl RPMI. Mice were treated with Buprenorphine and Ibuprofen for 3 days, and monitored for endpoint symptoms. Animals were euthanized when the tumors reached 1 cm3 or 10% of the body weight was lost. Resected tumors were minced and incubated with Collagenase IV (StemCell Technologies) containing DNAseI (Roche) for 30 min at 37 °C. Single cells were strained through 70 μm filter (FisherBrand) and stained with 1:1000 diluted LIVE/DEAD Fixable Stains (ThermoFisher) for 10 min on ice. Samples were acquired with BD Fortessa.

For in vivo cell cycle analysis upon macrophage mitochondrial transfer in Figure 5d: 8–12 week old B6N.Cg-Gt(ROSA)26Sortm1(CAG-EGFP*)Thm/J (also known as MitoTag mice, The Jackson Laboratory stock 032675 Fecher et al., 2019 and B6.129P2-Lyz2tm1(cre)Ifo/J) (also known as LysMcre mice, The Jackson Laboratory, stock 004781) were ordered and crossed accordingly, producing offspring which were heterozygous for both transgenes. These heterozygous siblings were crossed to produce both experimental (MitoTag/cre) and control (WT/cre) animals in the same litter. 250,000 Mito-RFP E0071 cells were injected into the mammary fat pad at a 1:1 ratio of matrigel (Corning) and sterile 1 x PBS into 6–8 week old mice of the appropriate genotypes. When the largest tumor reached 1cm3 the mice were euthanized and the tumors were homogenized as above and processed for Ki67 flow cytometry as listed in ‘Quantification of Ki67 and DNA content’.

Agent-based model for impact of mitochondrial transfer on cell division over time

The agent based model performs a Monte-Carlo simulation of individual cell ‘agents’ over time. At every timepoint, cells increase in mass, m, over the simulated time interval Δt according to an exponential growth law:

mt+1=mt+kmtΔt (1)

here k is the exponential growth constant. Over every time interval, a fraction of cells, fΔt , gain transferred mitochondria:

fΔt=fΔtTd (2)

where f is the overall fraction of the population gaining mitochondria (set to 5% based on our observation that this fraction of the population has transferred mitochondria) over the cell doubling time, Td.

The exponential growth constant, k, is then equal to k0, the baseline growth rate, for cell agents without transferred mitochondria, or k0r, where r is the factor of growth rate increase for cells with transferred mitochondria.

If the mass of a cell is greater than double its baseline mass, then it divides into two new daughter cells, each at half the mass of the parent, that are then tracked in the simulation. We assume that half the population loses transferred mitochondria (and the associated growth increase) with every division.

The mass of the population, mP, is then found by summing the mass of all individual cell agents at a given time.

This result can be compared to the overall final tumor mass in the baseline case, mB, after a given number, d, of doublings based on pure exponential growth:

mB=m0edln2 (3)

This result is plotted in Figure 5—figure supplement 2 for the case of 5% of the tumor cell population receiving macrophage mitochondria.

Data and materials availability

The code for QPI analysis is available on GitHub (https://github.com/Zangle-Lab/Macrophage_tumor_mito_transfer).

Single-cell RNA-sequencing data are available in GEO accession number GSE181410. The code for single-cell RNA-sequencing analysis is available on GitHub (https://github.com/rohjohnson-lab/kidwell_casalini_2021; RRID:SCR_002630 (Version 1)).

All other data are available in the main text or in the Supplementary Data.

Image analysis

All images taken with the Airyscan detector on the Zeiss LSM 880 were subjected to deconvolution using the Zen software (Carl Zeiss) with 'auto' settings (referred to as AiryScan processed). Maximum intensity projections of selected z-planes were generated using Zen or FIJI software (Schindelin et al., 2012). Linear adjustments to the brightness and contrast were made using FIJI. Images were cropped and panels were assembled using Adobe Photoshop and Illustrator, respectively (Adobe, Inc).

Graphical representations and statistical analysis

All graphs were generated using Prism software (v9, GraphPad). All graphs show mean with standard error of the mean. Statistical analyses were performed using both Excel (v16.51, Microsoft) and Prism. Statistical tests used and p-value ranges are indicated in each figure legend. Nested statistical tests were used to take into account the technical replicates within each biological replicate in the analysis of variance tests. Flow cytometry data and representations were analyzed and generated using FlowJo software (v10.7, BD). Welches t-test was used when the goal was to compare mean values of data with normal distribution, and Mann-Whitney analyses was applied when the data was not normally distributed. Two-way ANOVA was utilized when comparing how two independent variables influence a dependent variable. All statistical methodologies were performed under the guidance of biostatistician, Dr. Kenneth M. Boucher.

Acknowledgements

We thank Wes Sundquist and all members of the Roh-Johnson lab for helpful discussions and edits to this manuscript; ARUP Laboratories for providing leukofilters; James Carrington, Dong Hwi Bae, and Joshua Monts for technical support; Hannah Young for help with data analysis; Alan Aderem and Elizabeth Gold for their mentorship to GSO; and Kenneth M Boucher for help with statistics. We also thank Sadie Johnson for help with animal care, and Kristin Weber Bonk and Ruth Keri for help with animal experiments. We also thank the Huntsman Cancer Institute Cancer Center Shared Resources; the University of Utah Flow Cytometry Core for technical assistance; and the University of Utah Cell Imaging Core for use of the Leica Yokogawa CSU-W1 spinning disc confocal microscope.

Appendix 1

Appendix 1—key resources table.

Reagent type (species) or resource Designation Source or reference Identifiers Additional information
strain, strain background (M. musculus) wildtype C57BL/6 J The Jackson Laboratory Stock #000664
strain, strain background (M. musculus) mito:mKate2 mouse
Tg(CAG-mKate2)1Poche/J
The Jackson Laboratory Stock 032188
strain, strain background (M. musculus) LysM-Cre mouse
B6.129P2-Lyz2tm1(cre)Ifo/J
The Jackson Laboratory Stock 004781
strain, strain background (M. musculus) Lox-stop-lox-MitoTag mouse
B6N.Cg-Gt(ROSA)26Sortm1(CAG-EGFP*)Thm/J
The Jackson Laboratory Stock 032675
cell line (Homo-sapiens) MDA-MB-231 American Type Culture Collection HTB-26
cell line (Homo-sapiens) MDA-MB-468 American Type Culture Collection HTB-132
cell line (Homo-sapiens) A375 American Type Culture Collection CRL-1619
cell line (Homo-sapiens) THP-1 American Type Culture Collection TIB-202
cell line (Homo-sapiens) MCF10a American Type Culture Collection CRL-10317
cell line (M. musculus) E0771 American Type Culture Collection CRL-3461
transfected construct (Homo-sapien) pLPCX mito-Grx1-roGFP2 Addgene 64977
transfected construct (S. cerevisiae) pLPCX mito-roGFP2-Orp1 Addgene 64992
antibody BV711-CD11b (mouse anti-human, monoclonal) Biolegend 301344 1:20-1:40
Used for flow cytometry
antibody PE anti-human CD326 (EpCAM) Antibody
(mouse andti-human, monoclonal)
Biolegend 369806 1:40
Used for flow cytometry
antibody APC-Ki67
(mouse anti-human, Monoclonal)
ThermoFisher 17-5699-42 1:20 – 1:40
Used for flow cytometry
antibody anti-GFP (Chicken, polyclonal) Abcam AB13970, 1:500
antibody anti-RFP (rabbit, polyclonal) Abcam AB62341 1:1000
antibody Alexa Fluor 488 AffiniPure (Goat anti-Chicken, polyclonal) Jackson ImmunoResearch 103-545-155 1:500
antibody IgG (H+L) (Cross-Adsorbed Goat anti-Rabbit Alexa Fluor 555, polyclonal) Invitrogen A21428 1:500
recombinant DNA reagent Mito-mEm: pLKO.1 mito-mEmerald This paper Addgene, 174548 Lentiviral construct to transfect and express fluorescently-tagged mitochondria
recombinant DNA reagent Mito-RFP: pLKO.1 mito-TagRFP-T This paper Addgene,
174543
Lentiviral construct to transfect and express fluorescently-tagged mitochondria
recombinant DNA reagent mEmerald-TOMM20: pLKO.1 mEmerald-TOMM20-N-10 This paper Addgene,
54282
Lentiviral construct to transfect and express fluorescently-tagged mitochondria
recombinant DNA reagent mCherry-TOMM20: pLKO.1 mCherry-TOMM20-N-10 This paper Addgene,
55146
Lentiviral construct to transfect and express fluorescently-tagged mitochondria
recombinant DNA reagent Mito-KR: pLKO.1 3xHA-KillerRed-OMP25 This paper Addgene,
174544
Lentiviral construct to
transfect and express mitochondrially-localized KillerRed
recombinant DNA reagent ERK-KTR-mRuby:
pLentiPGK Blast DEST ERKKTRmRuby2
Addgene 90231 Lentiviral construct to
transfect and express ERK Kinase Translocation reporter
recombinant DNA reagent ERK-KTR-Clover:
pLentiPGK Puro DEST ERKKTRClover
Addgene 90227 Lentiviral construct to
transfect and express ERK Kinase Translocation reporter
recombinant DNA reagent Non-target-shRNA Sigma SHC002 Lentiviral construct to transfect and express non-target shRNA
recombinant DNA reagent DRP1-KD:
DRP1-shRNA
Sigma TRCN0000001097 Lentiviral construct to
transfect and knock down gene target HGNC ID 2973
sequence-based reagent Primer: DRP1-F This paper AGAAAATGGGGTGGAAGCAGA
sequence-based reagent Primer: DRP1-R This paper AAGTGCCTCTGATGTTGCCA
sequence-based reagent Primer: GAPDH-F This paper AGCCACATCGCTCAGACA
sequence-based reagent Primer: GAPDH-R This paper ACATGTAAACCATGTAGTTGAGGT
peptide, recombinant protein GM-CSF Peprotech 300–03 20 ng/mL
peptide, recombinant protein IFN-γ Peprotech 3000–02 20 ng/mL
peptide, recombinant protein IL-4 Peprotech 200–04 20 ng/mL
peptide, recombinant protein IL-13 Peprotech 200–13 20 ng/mL
commercial assay or kit eBioscience Foxp3/Transcription Factor Staining Buffer Set ThermoFisher 00-5523-00
commercial assay or kit Polyplus-transfection jetPRIME DNA/siRNA transfection kit Genesee Scientific 55–131 Used to transfect pLPCX mito-Grx1-roGFP2 and pLPCX mito-roGFP2-Orp1 probes
commercial assay or kit MitoTracker Deep Red ThermoFisher M22426 Used at 25 nM
commercial assay or kit TMRM:
Tetramethylrhodamine, Methyl Ester, Perchlorate
ThermoFisher T668 Used at 100 nM
commercial assay or kit LysoTracker Blue ThermoFisher L7525 Used at 75 nM
commercial assay or kit MemBrite 640/660 Biotium 30097 Used at 1:1000
commercial assay or kit DCFDA:
Carboxy-H2DCFDA
ThermoFisher C400 Used at 5μM
chemical compound, drug ERKi:
SCH772984
SelleckChem 7101 Used at 1 µM
chemical compound, drug PMA:
Phorbol 12-myristate 13-acetate
SelleckChem S7791 Used at 100 nM (cancer cell treatment) and 162 nM (THP1 differentiation)
chemical compound, drug MitoTEMPO Cayman Chemical 16621 Used at 100 µM
software, algorithm QPI analyses This Paper https://github.com/Zangle-Lab/Macrophage_tumor_mito_transfer
software, algorithm Single-cell RNA-sequencing This paper GEO accession number: GSE181410 (RRID:SCR_002630 (version number 1))
https://github.com/rohjohnson-lab/kidwell_casalini_2021

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Contributor Information

Minna Roh-Johnson, Email: roh-johnson@biochem.utah.edu.

Lydia WS Finley, Memorial Sloan Kettering Cancer Center, United States.

Benoît Kornmann, University of Oxford, United Kingdom.

Funding Information

This paper was supported by the following grants:

  • National Institutes of Health R37CA247994 to Minna Roh-Johnson.

  • U.S. Department of Defense W81XWH-20-1-0591 to Minna Roh-Johnson.

  • The Mary Kay Foundation 10-19 to Minna Roh-Johnson.

  • National Institutes of Health R00CA190836 to Chelsea U Kidwell, Minna Roh-Johnson.

  • National Institutes of Health F31CA250317 to Joseph R Casalini.

  • National Institutes of Health K99 CA248611 to Defne Bayik.

  • National Institutes of Health TL1 TR002549 to Dionysios C Watson.

  • Lerner Research Institute, Cleveland Clinic to Justin D Lathia.

  • Case Comprehensive Cancer Center, Case Western Reserve University to Justin D Lathia.

  • VeloSano Bike Ride to Defne Bayik, Dionysios C Watson, Justin D Lathia.

  • U.S. Department of Defense W81XWH1910065 to Thomas A Zangle.

  • National Institutes of Health U54CA224076 to Alana L Welm.

  • Breast Cancer Research Foundation to Alana L Welm.

Additional information

Competing interests

No competing interests declared.

No competing interests declared.

Author contributions

Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing.

Conceptualization, Resources, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing.

Conceptualization, Data curation, Formal analysis, Investigation, Methodology.

Resources, Methodology.

Data curation, Software, Formal analysis, Methodology.

Formal analysis, Validation, Methodology.

Formal analysis, Methodology.

Resources.

Funding acquisition.

Resources, Methodology.

Writing – review and editing.

Resources, Methodology.

Resources, Data curation, Software, Formal analysis, Methodology.

Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing.

Ethics

All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) at the University of Utah (PHS Assurance Registration Number: A3031-01; USDA Registration Number: 87-R-0001; protocol #19-12001) and at the Cleveland Clinic (protocol #2179). In accordance to approved protocol, all animals were anesthetized appropriately to assure maximum comfort throughout the duration of procedures. When tumors were grown to approved volumes, mice were humanely euthanized with slow C02 gas exchange for 5 minutes.

Additional files

MDAR checklist

Data availability

The code for QPI analysis is available on GitHub (https://github.com/Zangle-Lab/Macrophage_tumor_mito_transfer; copy archived at ZangleLab, 2023) for Figure 1.Single-cell RNA-sequencing data are available in GEO accession number GSE181410. The code for single-cell RNA-sequencing analysis is available on GitHub (https://github.com/rohjohnson-lab/kidwell_casalini_2021; copy archived at rohjohnson-lab, 2023) for Figure 1.

The following previously published dataset was used:

Roh-Johnson M, Greiner D. 2021. Macrophage and MDA-MB-231 coculture and mitochondrial transfer. NCBI Gene Expression Omnibus. GSE181410

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Editor's evaluation

Lydia WS Finley 1

This important work demonstrates that the transfer of dysfunctional mitochondria stimulates proliferation in recipient cancer cells by serving as a signal to induce reactive oxygen species production that in turn activates signaling pathways that control cell cycle. Compelling cell biology assays including rigorous microscopy with elegant reporters track the function and fate of transferred mitochondria in recipient cells. The work is relevant to the study of mitochondria, cancer, and immune cells and will be of broad interest to cell biologists and biochemists.

Decision letter

Editor: Lydia WS Finley1

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Transferred mitochondria act as a signaling source promoting proliferation" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Benoît Kornmann as the Senior Editor.

As you will see below, the reviewers found the work to be of potential interest but raised significant concerns that would require additional experimentation prior to consideration of a revised version. The reviewers have opted to remain anonymous.

All three reviewers found the paper to have interesting implications for many fields-- from mitochondrial biology to cancer biology and beyond-- and to employ multiple convincing methods to demonstrate transfer of mitochondria with potential to alter recipient cell function. At the same time, all reviewers raised similar concerns about the strength and validity of the proposed model. A key question raised by all 3 reviewers is how the transferred mitochondria produce ROS in the absence of a membrane potential. A related concern is that mitoTEMPO, the antioxidant used to show that quenching ROS dissipates the pro-mitogenic signal of transferred mitochondria, relies on membrane potential to accumulate within mitochondria. Therefore, whether the ROS are made specifically by transferred mitochondria to control cell signaling is not fully demonstrated at this time. Revisions to address these central questions are discussed below. The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

Overall, the reviewers each shared several major concerns. For completeness, I am including the entire reviewer remarks below to provide full context for all requested revision. Here, I summarize the three key essential revision requirements alongside other major/minor points that should be addressed. Reviewer points where data would be welcome, but not required, are specifically noted at the end.

Essential questions:

1. How can defective mitochondria produce ROS? If they do not have membrane potential, are they respiring? If not, do they have functional electron transfer reactions that can generate ROS? As mitoTEMPO accumulates in mitochondria as a result of membrane potential, the relevance of these experiments are not clear. (Please see full comments below for more reviewer context.)

2. A related questions is whether ROS is generated specifically by the transferred mitochondria? Use of mitoTEMPO in quenching ROS may illustrate that the ROS is not coming from transferred mitochondria, or the transferred mitochondria regain membrane potential, as this antioxidant like other triphenylphosphonium-based antioxidants accumulate based on membrane potential. The authors partially address this with barcoded biosensors, but this hampers the ROS-arguments in the paper, and the authors should readdress interpretations. Related, ROS quenching and ERK inhibition only affect proliferation when it is done in transferred mitochondria. Why don't ROS and ERK affect proliferation in control cells? (See comments by Reviewer #1 and #2, below.)

3. How much of the transferred mitochondria and/or mitochondrial ROS is beneficial? (See full comment from Reviewer #3 below.)

Other essential reviewer comments to address:

– Figure 1c. Why does the recipient cell need to be cancerous (referring to the MCF10A experiment). Is there sufficient experimental evidence for this claim?

– Figure 1 – Supplement 2a. In line with ROS signaling in the following experiments – were the proliferative program observed in Figure 1 – Sup 2a ROS dependent?

– The authors show in Figure 2 that it takes 48 h for mitochondria to become oxidized. In Figure 1 it appears that the proliferation benefit occurs as early as 24 h of coculture. How do the authors reconcile these timescales?

Reviewer #1 (Recommendations for the authors):

Questions:

– One major question is how do mitochondria without membrane potential induce ROS? Do they have functional electron transfer reactions that are producing ROS?

– The authors show in Figure 2 that it takes 48 h for mitochondria to become oxidized. In Figure 1 it appears that the proliferation benefit occurs as early as 24 h of coculture. How do the authors reconcile these timescales?

­

– I'm puzzled by the observation that ROS quenching and ERK inhibition only affect proliferation when it is done in transferred mitochondria. Why don't ROS and ERK affect proliferation in control cells?

Reviewer #2 (Recommendations for the authors):

The manuscript will be strengthened if the following substantial revisions based on the following points.

Methods

The authors include sufficient experimental detail and utilize appropriate model systems.

Results

Figure 1c. Why does the recipient cell need to be cancerous (referring to the MCF10A experiment). Is there sufficient experimental evidence for this claim. Can the authors speculate on the regulation of mitochondrial uptake by cancer cells, specifically, in vitro?

Figure 1g. The authors aim to isolate mitochondria from macrophages and test the ability of isolated mitochondria in promoting proliferation in cancer cell lines. The authors performed a crude mitochondrial isolation protocol here, without sucrose or percoll gradient ultracentrifugation to purify mitochondria from associated endoplasmic reticulum. The authors do not illustrate the extent of purification of the isolated mitochondria. This makes the data difficult to interpret, and the effects of ER contamination on proliferation are not controlled for. We suggest the authors perform this experiment with an ultracentrifuge-purified sample. Alternatively, mito-tag approaches can be used to IP intact mitochondria from cells.

Figure 1 – Supplement 2a. The authors perform single-cell RNAseq in MDA-MB-231 +/- macrophage mitochondria. Can the authors comment on the duration of mitochondrial uptake in these cells prior to RNAseq? Is it an acute proliferative response (gene expression program) to the uptake of mitochondria (short-term), or a robust adaptation (long-term). The authors indicate that the daughter cells exhibit sustained increases in growth rates – can the authors then indicate the time of RNAseq? Also, in line with ROS signaling in the following experiments – were the proliferative program observed in Figure 1 – Sup 2a ROS dependent?

Figure 2. General comment regarding transferred mitochondria without membrane potential. Are these mitochondria respiring? Where is the source of ROS coming from, and how is the membrane potential dissipated if these mitochondria are in fact respiring? Is this through reverse ATP synthase activity as it occurs in mitochondrial deleted cells? Can the authors illustrate the capacity at which these macrophage-mitochondria are respiring? Can the authors show that the ROS is specific to the transferred mitochondria and not an off-target ROS generation? Use of mitoTEMPO in quenching ROS may illustrate that the ROS is not coming from your transferred mitochondria, or the transferred mitochondria regain membrane potential. This antioxidant, and other triphenylphosphonium-based antioxidants accumulate based on membrane potential. The authors partially address this with barcoded biosensors, but this hampers the ROS-arguments in the paper, and the authors should readdress interpretations.

Figure 3. Similar as figure 2. The authors illustrate activation of ERK by photobleaching induced ROS. Although this illustrates that ROS activates ERK in this system, the authors do not illustrate that this ROS originates from macrophage mitochondria. As the authors mention, it is known that ROS induces ERK signaling. This section appears to further validate known mechanisms of ERK activation without connecting to the transferred mitochondria.

Figure 4. The authors illustrate that M2-macrophages exhibit enhanced mitochondrial transfer efficiency than M1. This supports the notion that M2 macrophages are pro-tumorigenic, here by a novel mechanism. Further data illustrating mitochondrial fission as an important regulator of the transfer process, as DRP1 knockdown with shRNA attenuates transfer.

Reviewer #3 (Recommendations for the authors):

Overall, the paper is convincing of its primary points, but expounding on some aspects is warranted to contextualize these findings with respect to the dose response of the effects and to address other studies on mitochondrial transfer in the literature:

1) How much transferred mitochondria and/or mitochondrial ROS is beneficial?

While the benefits of ROS in some contexts have been increasingly appreciated, ROS are also well known to cause deleterious effects at higher doses. The authors conclude that transferred mitochondria promote proliferation through mitochondrial ROS activation of ERK, but some understanding of the boundaries of this effect would help with interpretation. Some potential approaches to address this issue could include: Are there dose responsive effects with respect to proliferation or ERK signaling amongst cells with different numbers or volumes of transferred mitochondria? Is there a dose response to the cell cycle changes from macrophage mitochondria bath dosages corresponding to the number of mitochondria transferred? What range of mito-KillerRed activation is beneficial, and at what point is it deleterious?

2) How do we reconcile the finding that transferred macrophage mitochondria are persistently dysfunctional?

As the authors noted, the literature has focused on situations where mitochondrial transfer can repopulate functional mitochondria in cancer cells with endogenously dysfunctional mitochondria, but here the authors conclude that transferred mitochondria are persistently dysfunctional in recipient cells. While this discrepancy is not likely to be entirely solved here, some simple experiments could help put context on the salient differences between studies by addressing how their biological system might influence the results: Can transfer of macrophage mitochondria reconstitute mitochondrial function of rho zero cells? Does transfer of mitochondria amongst 231 cell populations (e.g.. transfer of 231 cell mitochondria expressing mito-RFP to 231 cells expressing mito-mEmerald) also result in persistently dysfunctional mitochondria in recipient cells? Do mEmerald expressing macrophages have functional mitochondria prior to mitochondrial transfer?

eLife. 2023 Mar 6;12:e85494. doi: 10.7554/eLife.85494.sa2

Author response


Essential revisions:

Essential questions:

1. How can defective mitochondria produce ROS? If they do not have membrane potential, are they respiring? If not, do they have functional electron transfer reactions that can generate ROS? As mitoTEMPO accumulates in mitochondria as a result of membrane potential, the relevance of these experiments are not clear. (Please see full comments below for more reviewer context.)

We cannot say for certain that transferred mitochondria generate the ROS or if it is generated elsewhere in the cell. However, our rationale for the mito-KillerRed experiments is to experimentally test whether inducing small amounts of ROS is sufficient to promote cell division, regardless of the source. We used mitochondrially localized KillerRed as we wanted to control for the photobleaching procedure itself – ie. if KillerRed were spatially localized, then we can photobleach a KillerRed-negative region as a control. It is not possible to quantify the exact amount of ROS in cancer cells with macrophage mitochondria, but our experiments show that cancer cells with macrophage mitochondria have increased intracellular ROS, the biosensor experiments suggest that ROS is in a localized region at transferred mitochondria (Figure 2c,d), and that quenching ROS specifically inhibits proliferation of cancer cells with macrophage mitochondria, without affecting cancer cell proliferation more broadly (Figure 2f). From these results, we aimed to produce small amounts of ROS by photobleaching small 2µm x 2µm regions of interest, and determining whether this small amount of ROS production is sufficient to cause cell division, regardless of where the ROS is generated. If we performed similar experiments with cytoplasmic KillerRed (not mitochondrially-localized), we would expect the same response, although the negative control photobleaching would be much harder to perform, which is why we opted to use the mitochondrially-localized KillerRed. The outcome of this experiment is that inducing small amounts of ROS is sufficient to induce proliferation.

Second, it appears that the mito-Grx1-roGFP2 sensors are encoded in the recipient cells; how do these sensors then become localized to the transferred mitochondria?

This is a great question, and one that we have thought about as well. Yes, the mito-Grx1-roGFP2 sensor is encoded in the recipient cells. The construct contains an MTS from an ATP synthase that targets it to the mitochondria. Due to the reduced membrane potential, we do not know whether the sensor is imported into the mitochondria, although it is possible that some of the mitoGrx1-roGFP2 sensor is inserted into the transferred mitochondria, if the transferred mitochondria retain very low levels of membrane potential (low enough to not be detected by the membrane potential-sensitive dyes). Regardless of whether the sensor is imported into the mitochondria, we interpret our findings to suggest that the Grx1-roGFP2 sensor is targeted to the transferred mitochondria, and the sensor is reading out the oxidized versus reduced forms of Grx1 at that site, even if it is not imported into the mitochondria. Our understanding from the literature and from discussions with our metabolism colleagues is that the sensor does not need to be inserted into the transferred mitochondria to show the redox state of Grx1 in the vicinity of the transferred mitochondria, and that the strength of protein insertion is dependent on the specific MTS and the protein it is fused to (Schafer, Bozkurt et al. 2022). For example, PINK contains an MTS, and can still localize and be processed by mitochondria in the absence of membrane potential (Becker, Richter et al. 2012). PINK1 can also be retained at the outer mitochondrial membrane in the absence of an MTS altogether, thereby suggesting that mitochondrial insertion is not required for maintained mitochondrial localization (Zhou, Huang et al. 2008, Liu, Vives-Bauza et al. 2009, Weihofen, Thomas et al. 2009). Our work shows that reactive oxygen species accumulate at the site of transferred mitochondria using two different biosensors. We think that the biosensor is constantly in flux, with a constant flow of Grx1-roGFP2 targeted to mitochondria, and becoming oxidized at the transferred mitochondria. We tried to test this hypothesis by performing FRAP (fluorescence recovery after photobleaching) experiments of the biosensor at transferred mitochondria and quantifying fluorescence recovery over time. We observed recovery of the biosensor at transferred mitochondria, with the biosensor primarily showing the oxidized version of Grx1 at this site, but due to the dynamic nature of the mitochondria, the transferred mitochondria were hard to track without overlapping with endogenous mitochondria, which distorted the quantification. As a result, we could not reliably quantify the FRAP. However, we have included representative images at time points from these experiments before and after photobleaching. The cancer cell is expressing mito-Grx1-roGFP2. Macrophage mitochondria are red, and an arrowhead marks the macrophage mitochondria that we followed after photobleaching. The zoom panels in Author response image 1 highlights the macrophage mitochondria targeted for photobleaching as a merged image (showing red transferred mitochondria outlined in gray; yellow oxidized-Grx1; and green reduced-Grx1), and then an oxidized-Grx1 only panel to better visualize this state. Before photobleaching the sensor, we can visualize the oxidized form of mito-Grx-roGFP2 at the site of transferred mitochondria in “A”. We then photobleached the sensor at transferred mitochondria in “B”. We know that we photobleached the sensor at this site, as we visualized decreased levels of oxidized Grx1-roGFP2 in the right-most panel of “B”. 40 seconds after photobleaching, the sensor returns to the site of transferred mitochondria in “C”. To ensure that the oxidized form of mito-Grx1-roGFP2 is tracking with the transferred macrophage mitochondria, we also looked another 5 seconds later, and can still visualize enriched oxidized Grx1 at that site in “D”. We interpret these preliminary results to suggest that the sensor is in flux and can continually target to transferred mitochondria.

Author response image 1.

Author response image 1.

Thus, while we cannot comment on whether or how much of the sensor is inserted into the transferred mitochondria, nor can we perform experiments to quantify the extent of Grx1-roGFP2 processing by these mitochondria due to the lack of protein input for biochemical assays, we interpret these data as ROS accumulates at the site of transferred mitochondria, which in itself was an unexpected and exciting discovery, and a central finding of the work.

2. A related questions is whether ROS is generated specifically by the transferred mitochondria? Use of mitoTEMPO in quenching ROS may illustrate that the ROS is not coming from transferred mitochondria, or the transferred mitochondria regain membrane potential, as this antioxidant like other triphenylphosphonium-based antioxidants accumulate based on membrane potential. The authors partially address this with barcoded biosensors, but this hampers the ROS-arguments in the paper, and the authors should readdress interpretations. Related, ROS quenching and ERK inhibition only affect proliferation when it is done in transferred mitochondria. Why don't ROS and ERK affect proliferation in control cells? (See comments by Reviewer #1 and #2, below.)

Regarding the ROS quenching and ERK results, we specifically sought quenching and inhibitor concentrations that inhibit/quench the target, but have little effect on cancer cell monoculture proliferation. We performed these critical experiments to specifically test whether ROS/ERK inhibition affects the proliferative capacity of cancer cells with macrophage mitochondria, as opposed to proliferation generally. We show representative ERKi data in Author response image 2 – We tested 5 different ERKi concentrations, and evaluated both inhibition of ERK activity (as measured by flow cytometry quantifying the activated phosphorylated ERK, p-ERK, in “Author response image 2A”), as well as changes to the G2/M phase of the cell cycle (black bar in graph in “Author response image 2B”). These preliminary results showed that both 0.3µM and 1µM ERKi inhibited ERK activity, but did not affect the G2/M phase of the cell cycle in cultured 231 cancer cells alone (n=1 biological replicate; n=3 technical replicates). Thus, we used the 1 µM ERKi for subsequent coculture assays in the manuscript (Figure 3e,f; each with n=3 biological replicates). We have made modifications to the text to better articulate this important point.

Author response image 2.

Author response image 2.

3. How much of the transferred mitochondria and/or mitochondrial ROS is beneficial? (See full comment from Reviewer #3 below.)

This is an interesting question. We have addressed this question by performing some of the experiments suggested by this reviewer. To determine whether there are dose responsive effects with respect to proliferation or ERK signaling amongst cells with different amounts of transferred mitochondria, we analyzed populations of cancer cells with either “high” or “low” amounts of transferred macrophage mitochondria. These “high” and “low” designations were determined by taking into the account the median FITC fluorescence intensity for cancer cells with transferred mitochondria, while maintaining equal numbers of cancer cells in both the “high” and “low” population to avoid calculating percentages on small numbers of cells (Author response image 3A for representative gating). We then analyzed the percentages of cells in the different phases of the cell cycle (Author response image 3B, statistics shown specifically for the proliferative G2/M phase of the cell cycle). Both the “high” and “low” populations showed an increase in the percentage of cells in the G2/M phase of the cell cycle compared to the “no transfer” population, consistent with what we report in the manuscript, but we found no difference between the “high” and “low” populations suggesting that the amount of macrophage mitochondrial transfer to cancer cells observed in our system did not affect cell cycle stages in a dose-dependent manner.

Author response image 3. A.

Author response image 3.

Representative gating strategy for “low” vs “high” macrophage mitochondrial transfer in macrophage/cancer cell cocultures. B. Cell cycle analysis for populations in (A). 2-way ANOVA, n=2 biological replicates, p<0.001. C. ERK-KTR analysis with imagestream, n=3 biological replicates, 1-way ANOVA, p<0.0001. D. Scatterplot of ERK-KTR and mitochondrial transfer mean fluorescence intensity (MFI). Each dot is a cell. n=7,966 cells. Correlation R2 value: 3.261e-005. E. Representative gating strategy for “low” vs “high” macrophage mitochondrial uptake by cancer cells. F. Cell cycle analysis for populations in (E). 2-way ANOVA, n=3 biological replicates, p<0.001.

We then performed similar analysis for ERK activation, in which we used the ERK-KTR biosensor to measure the cytoplasmic/nuclear ratios of ERK, with higher cytoplasmic/nuclear ratios indicating higher ERK activity. Similar to our proliferation results, we did not observe differences in ERK activity between the “high” and “low” mitochondrial transfer populations (Author response image 3C). With the ERK-KTR biosensor, we are also able to quantify ERK activity on a cell-by-cell basis, thus we analyzed each cell and graphed ERK activity (y-axis) with respect the fluorescence intensity of mitochondrial transfer in the same cell (x-axis) (Author response image 3D). We did not observe a positive correlation between the amount of mitochondrial transfer and ERK activity (R2 value: 3.261e-005).

Finally, we determined whether there was a dose response to cell cycle changes with macrophage mitochondrial bath applications. Similar to our analysis with cocultures in Figure A, we divided the cancer cell population into “high” vs “low” mitochondrial uptake (Figure E), and analyzed cell cycle stages (Figure F). We did not observe dose-dependent cell cycle changes in response to macrophage mitochondrial uptake.

Together, these results suggest that cancer cells with macrophage mitochondria exhibit increased ERK activity and increased proliferation, and that the increased ERK activity and proliferation does not show a dose-dependent response to mitochondrial transfer. We hypothesize that the mitochondrial transfer, and the subsequent ROS accumulation, that we observe within this system show beneficial (proliferation-promoting) effects, and is not within the boundaries of inducing deleterious effects.

Consistent with this hypothesis, previous reports using KillerRed either induce cell death or generate phototoxic damage (Bulina, Chudakov et al. 2006, Li, Fang et al. 2019). These approaches typically use high laser settings, irradiate the whole cell, and use long and continuous illumination times in the order of several minutes (Bulina, Chudakov et al. 2006, Williams, Bejjani et al. 2013, Kuznetsova, Shirmanova et al. 2015, Li, Fang et al. 2019). Our approaches with mito-KillerRed use small, 2 m x 2 m, regions of interest and illumination on the 5-10 seconds time scale, and thus suggest that we are likely generating low levels of ROS (as indicated by Figure 3 – Figure S5), and not near the ROS levels that induce cell death.

We did not include these data into the manuscript as we were not clear what additional insights the findings added to the work given that we did not observe a dose-dependent effect, however we would be happy to do so, if the reviewers prefer.

Other essential reviewer comments to address:

– Figure 1c. Why does the recipient cell need to be cancerous (referring to the MCF10A experiment). Is there sufficient experimental evidence for this claim?

We do not have evidence that the recipient cell needs to be cancerous to receive macrophage mitochondria. The MCF10A result shows that macrophages exhibit decreased transfer efficiencies to MCF10A than the other three malignant cell lines we tested. We do think that macrophage mitochondrial transfer can occur to non-malignant cell lines as illustrated in other published work (Nicolas-Avila, Lechuga-Vieco et al. 2020, Brestoff, Wilen et al. 2021, Liu, Wu et al. 2022, van der Vlist, Raoof et al. 2022, Yang, Yokomori et al. 2022), but it is not clear whether the mechanism of mitochondrial dysfunction and ROS accumulation occurs in these systems. We have adjusted the language in the text to reflect this point.

– Figure 1 – Supplement 2a. In line with ROS signaling in the following experiments – were the proliferative program observed in Figure 1 – Sup 2a ROS dependent?

The single cell RNA sequencing results were unfortunately not performed in the presence of mitoTEMPO. While we are unable to answer this specific question with the scRNA sequencing results, we were able to show complementary experiments that the proliferative response observed in cancer cells with macrophage mitochondria can be ameliorated with the addition of mitoTEMPO with a cell-based assay (Figure 2f).

– The authors show in Figure 2 that it takes 48 h for mitochondria to become oxidized. In Figure 1 it appears that the proliferation benefit occurs as early as 24 h of coculture. How do the authors reconcile these timescales?

We apologize if it wasn’t clear. The result in Figure 2D with the mito-Grx1-roGRP2 was within 24 hours, which is the same time frame as the proliferation phenotype (also at 24 hours). We have made the time point clearer in the figure legend.

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Roh-Johnson M, Greiner D. 2021. Macrophage and MDA-MB-231 coculture and mitochondrial transfer. NCBI Gene Expression Omnibus. GSE181410

    Supplementary Materials

    MDAR checklist

    Data Availability Statement

    The code for QPI analysis is available on GitHub (https://github.com/Zangle-Lab/Macrophage_tumor_mito_transfer; copy archived at ZangleLab, 2023) for Figure 1.Single-cell RNA-sequencing data are available in GEO accession number GSE181410. The code for single-cell RNA-sequencing analysis is available on GitHub (https://github.com/rohjohnson-lab/kidwell_casalini_2021; copy archived at rohjohnson-lab, 2023) for Figure 1.

    The following previously published dataset was used:

    Roh-Johnson M, Greiner D. 2021. Macrophage and MDA-MB-231 coculture and mitochondrial transfer. NCBI Gene Expression Omnibus. GSE181410


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